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- LICENSE.txt +111 -0
- README.md +42 -3
- USE_POLICY.md +52 -0
- chat_template.json +3 -0
- config.json +234 -0
- generation_config.json +13 -0
- model-00001-of-00037.safetensors +3 -0
- model-00002-of-00037.safetensors +3 -0
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- model-00013-of-00037.safetensors +3 -0
- model-00014-of-00037.safetensors +3 -0
- model-00015-of-00037.safetensors +3 -0
- model-00016-of-00037.safetensors +3 -0
- model-00017-of-00037.safetensors +3 -0
- model-00018-of-00037.safetensors +3 -0
- model-00019-of-00037.safetensors +3 -0
- model-00020-of-00037.safetensors +3 -0
- model-00021-of-00037.safetensors +3 -0
- model-00022-of-00037.safetensors +3 -0
- model-00023-of-00037.safetensors +3 -0
- model-00024-of-00037.safetensors +3 -0
- model-00025-of-00037.safetensors +3 -0
- model-00026-of-00037.safetensors +3 -0
- model-00027-of-00037.safetensors +3 -0
- model-00028-of-00037.safetensors +3 -0
- model-00029-of-00037.safetensors +3 -0
- model-00030-of-00037.safetensors +3 -0
- model-00031-of-00037.safetensors +3 -0
- model-00032-of-00037.safetensors +3 -0
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- model-00035-of-00037.safetensors +3 -0
- model-00036-of-00037.safetensors +3 -0
- model-00037-of-00037.safetensors +3 -0
- model.safetensors.index.json +0 -0
- preprocessor_config.json +25 -0
- special_tokens_map.json +23 -0
- tokenizer.json +3 -0
- tokenizer_config.json +2072 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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LICENSE.txt
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LLAMA 3.2 COMMUNITY LICENSE AGREEMENT
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Llama 3.2 Version Release Date: September 25, 2024
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any dispute arising out of this Agreement.
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README.md
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---
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---
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language:
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- en
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- de
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- fr
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- it
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- pt
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- hi
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- es
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- th
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library_name: transformers
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widget:
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- role: "user"
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content:
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- type: "text"
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text: "Where is this located in? What are other attractions nearby?"
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- type: "image_url"
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image_url:
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url: "https://huggingface.co/datasets/huggingface/release-assets/resolve/main/wat_arun.jpg"
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- role: "assistant"
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content: "The image depicts the Grand Palace in Bangkok, Thailand. The Grand Palace is a complex of buildings that served as the official residence of the King of Siam and the administrative seat of government for 150 years. It is one of the most popular tourist attractions in Bangkok and a must see for anyone visiting the city. <br> Some other attractions near the Grand Palace include: <br> * Wat Phra Kaew: This temple is located within the Grand Palace complex and is home to the famous Emerald Buddha statue. <br> * Wat Arum: This temple is located on the west bank of the Chao Phraya River and is known for its stunning architecture and beautiful views of the city. <br> * Wat Plo: This temple is located near the Grand Palace and is home to a large reclining Buddha statue. <br> * Lump hini Park: This park is located in the heart of Bangkok and offers a peaceful escape from the hustle and bustle of the city. <br> * Jim Thompson House: This museum showcases the life and work of Jim Thompson, an American businessman who helped revitalize the Thai silk industry in the 1950 s and 1960 s. Overall, the Grand Palace is a must- see attraction in Bangkok, and there are many other interesting places to visit in the area. "
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license: llama3.2
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pipeline_tag: image-text-to-text
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base_model: meta-llama/Llama-3.2-90B-Vision-Instruct
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tags:
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- facebook
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- meta
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- pytorch
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- llama
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- llama-3
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- abliterated
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- uncensored
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---
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# huihui-ai/Llama-3.2-11B-Vision-Instruct-abliterated
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This is an uncensored version of [meta-llama/Llama-3.2-90B-Vision-Instruct](https://huggingface.co/meta-llama/Llama-3.2-90B-Vision-Instruct) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it).
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This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.
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It was only the text part that was processed, not the image part.
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USE_POLICY.md
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**Llama 3.2** **Acceptable Use Policy**
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Meta is committed to promoting safe and fair use of its tools and features, including Llama 3.2. If you access or use Llama 3.2, you agree to this Acceptable Use Policy (“**Policy**”). The most recent copy of this policy can be found at [https://www.llama.com/llama3_2/use-policy](https://www.llama.com/llama3_2/use-policy).
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**Prohibited Uses**
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We want everyone to use Llama 3.2 safely and responsibly. You agree you will not use, or allow others to use, Llama 3.2 to:
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1. Violate the law or others’ rights, including to:
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1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:
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1. Violence or terrorism
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2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material
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3. Human trafficking, exploitation, and sexual violence
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4. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.
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5. Sexual solicitation
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6. Any other criminal activity
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1. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
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2. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services
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3. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices
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4. Collect, process, disclose, generate, or infer private or sensitive information about individuals, including information about individuals’ identity, health, or demographic information, unless you have obtained the right to do so in accordance with applicable law
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5. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama Materials
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6. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system
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7. Engage in any action, or facilitate any action, to intentionally circumvent or remove usage restrictions or other safety measures, or to enable functionality disabled by Meta
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2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama 3.2 related to the following:
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8. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State or to the U.S. Biological Weapons Anti-Terrorism Act of 1989 or the Chemical Weapons Convention Implementation Act of 1997
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9. Guns and illegal weapons (including weapon development)
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10. Illegal drugs and regulated/controlled substances
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11. Operation of critical infrastructure, transportation technologies, or heavy machinery
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12. Self-harm or harm to others, including suicide, cutting, and eating disorders
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13. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
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3. Intentionally deceive or mislead others, including use of Llama 3.2 related to the following:
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14. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
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15. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
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16. Generating, promoting, or further distributing spam
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17. Impersonating another individual without consent, authorization, or legal right
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18. Representing that the use of Llama 3.2 or outputs are human-generated
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19. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement
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4. Fail to appropriately disclose to end users any known dangers of your AI system
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5. Interact with third party tools, models, or software designed to generate unlawful content or engage in unlawful or harmful conduct and/or represent that the outputs of such tools, models, or software are associated with Meta or Llama 3.2
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With respect to any multimodal models included in Llama 3.2, the rights granted under Section 1(a) of the Llama 3.2 Community License Agreement are not being granted to you if you are an individual domiciled in, or a company with a principal place of business in, the European Union. This restriction does not apply to end users of a product or service that incorporates any such multimodal models.
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Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means:
|
46 |
+
|
47 |
+
|
48 |
+
|
49 |
+
* Reporting issues with the model: [https://github.com/meta-llama/llama-models/issues](https://l.workplace.com/l.php?u=https%3A%2F%2Fgithub.com%2Fmeta-llama%2Fllama-models%2Fissues&h=AT0qV8W9BFT6NwihiOHRuKYQM_UnkzN_NmHMy91OT55gkLpgi4kQupHUl0ssR4dQsIQ8n3tfd0vtkobvsEvt1l4Ic6GXI2EeuHV8N08OG2WnbAmm0FL4ObkazC6G_256vN0lN9DsykCvCqGZ)
|
50 |
+
* Reporting risky content generated by the model: [developers.facebook.com/llama_output_feedback](http://developers.facebook.com/llama_output_feedback)
|
51 |
+
* Reporting bugs and security concerns: [facebook.com/whitehat/info](http://facebook.com/whitehat/info)
|
52 |
+
* Reporting violations of the Acceptable Use Policy or unlicensed uses of Llama 3.2: [email protected]
|
chat_template.json
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- if strftime_now is defined %}\n {%- set date_string = strftime_now(\"%d %b %Y\") %}\n {%- else %}\n {%- set date_string = \"26 Jul 2024\" %}\n {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- Find out if there are any images #}\n{% set image_ns = namespace(has_images=false) %} \n{%- for message in messages %}\n {%- for content in message['content'] %}\n {%- if content['type'] == 'image' %}\n {%- set image_ns.has_images = true %}\n {%- endif %}\n {%- endfor %}\n{%- endfor %}\n\n{#- Error out if there are images and system message #}\n{%- if image_ns.has_images and not system_message == \"\" %}\n {{- raise_exception(\"Prompting with images is incompatible with system messages.\") }}\n{%- endif %}\n\n{#- System message if there are no images #}\n{%- if not image_ns.has_images %}\n {{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n {%- if tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n {%- endif %}\n {{- \"Cutting Knowledge Date: December 2023\\n\" }}\n {{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n {%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {%- endif %}\n {{- system_message }}\n {{- \"<|eot_id|>\" }}\n{%- endif %}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n' }}\n {%- if message['content'] is string %}\n {{- message['content'] }}\n {%- else %}\n {%- for content in message['content'] %}\n {%- if content['type'] == 'image' %}\n {{- '<|image|>' }}\n {%- elif content['type'] == 'text' %}\n {{- content['text'] }}\n {%- endif %}\n {%- endfor %}\n {%- endif %}\n {{- '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {{- \"<|eot_id|>\" }}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n"
|
3 |
+
}
|
config.json
ADDED
@@ -0,0 +1,234 @@
|
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|
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|
|
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|
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|
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|
|
|
|
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|
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|
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|
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|
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|
|
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|
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|
|
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"architectures": [
|
3 |
+
"MllamaForConditionalGeneration"
|
4 |
+
],
|
5 |
+
"image_token_index": 128256,
|
6 |
+
"model_type": "mllama",
|
7 |
+
"text_config": {
|
8 |
+
"_name_or_path": "",
|
9 |
+
"add_cross_attention": false,
|
10 |
+
"architectures": null,
|
11 |
+
"bad_words_ids": null,
|
12 |
+
"begin_suppress_tokens": null,
|
13 |
+
"bos_token_id": 128000,
|
14 |
+
"chunk_size_feed_forward": 0,
|
15 |
+
"cross_attention_hidden_size": null,
|
16 |
+
"cross_attention_layers": [
|
17 |
+
3,
|
18 |
+
8,
|
19 |
+
13,
|
20 |
+
18,
|
21 |
+
23,
|
22 |
+
28,
|
23 |
+
33,
|
24 |
+
38,
|
25 |
+
43,
|
26 |
+
48,
|
27 |
+
53,
|
28 |
+
58,
|
29 |
+
63,
|
30 |
+
68,
|
31 |
+
73,
|
32 |
+
78,
|
33 |
+
83,
|
34 |
+
88,
|
35 |
+
93,
|
36 |
+
98
|
37 |
+
],
|
38 |
+
"decoder_start_token_id": null,
|
39 |
+
"diversity_penalty": 0.0,
|
40 |
+
"do_sample": false,
|
41 |
+
"dropout": 0,
|
42 |
+
"early_stopping": false,
|
43 |
+
"encoder_no_repeat_ngram_size": 0,
|
44 |
+
"eos_token_id": [
|
45 |
+
128001,
|
46 |
+
128008,
|
47 |
+
128009
|
48 |
+
],
|
49 |
+
"exponential_decay_length_penalty": null,
|
50 |
+
"finetuning_task": null,
|
51 |
+
"forced_bos_token_id": null,
|
52 |
+
"forced_eos_token_id": null,
|
53 |
+
"hidden_act": "silu",
|
54 |
+
"hidden_size": 8192,
|
55 |
+
"id2label": {
|
56 |
+
"0": "LABEL_0",
|
57 |
+
"1": "LABEL_1"
|
58 |
+
},
|
59 |
+
"initializer_range": 0.02,
|
60 |
+
"intermediate_size": 28672,
|
61 |
+
"is_decoder": false,
|
62 |
+
"is_encoder_decoder": false,
|
63 |
+
"label2id": {
|
64 |
+
"LABEL_0": 0,
|
65 |
+
"LABEL_1": 1
|
66 |
+
},
|
67 |
+
"length_penalty": 1.0,
|
68 |
+
"max_length": 20,
|
69 |
+
"max_position_embeddings": 131072,
|
70 |
+
"min_length": 0,
|
71 |
+
"model_type": "mllama_text_model",
|
72 |
+
"no_repeat_ngram_size": 0,
|
73 |
+
"num_attention_heads": 64,
|
74 |
+
"num_beam_groups": 1,
|
75 |
+
"num_beams": 1,
|
76 |
+
"num_hidden_layers": 100,
|
77 |
+
"num_key_value_heads": 8,
|
78 |
+
"num_return_sequences": 1,
|
79 |
+
"output_attentions": false,
|
80 |
+
"output_hidden_states": false,
|
81 |
+
"output_scores": false,
|
82 |
+
"pad_token_id": 128004,
|
83 |
+
"prefix": null,
|
84 |
+
"problem_type": null,
|
85 |
+
"pruned_heads": {},
|
86 |
+
"remove_invalid_values": false,
|
87 |
+
"repetition_penalty": 1.0,
|
88 |
+
"return_dict": true,
|
89 |
+
"return_dict_in_generate": false,
|
90 |
+
"rms_norm_eps": 1e-05,
|
91 |
+
"rope_scaling": {
|
92 |
+
"factor": 8.0,
|
93 |
+
"high_freq_factor": 4.0,
|
94 |
+
"low_freq_factor": 1.0,
|
95 |
+
"original_max_position_embeddings": 8192,
|
96 |
+
"rope_type": "llama3"
|
97 |
+
},
|
98 |
+
"rope_theta": 500000.0,
|
99 |
+
"sep_token_id": null,
|
100 |
+
"suppress_tokens": null,
|
101 |
+
"task_specific_params": null,
|
102 |
+
"temperature": 1.0,
|
103 |
+
"tf_legacy_loss": false,
|
104 |
+
"tie_encoder_decoder": false,
|
105 |
+
"tie_word_embeddings": false,
|
106 |
+
"tokenizer_class": null,
|
107 |
+
"top_k": 50,
|
108 |
+
"top_p": 1.0,
|
109 |
+
"torch_dtype": "bfloat16",
|
110 |
+
"torchscript": false,
|
111 |
+
"typical_p": 1.0,
|
112 |
+
"use_bfloat16": false,
|
113 |
+
"use_cache": true,
|
114 |
+
"vocab_size": 128256
|
115 |
+
},
|
116 |
+
"torch_dtype": "bfloat16",
|
117 |
+
"transformers_version": "4.45.0.dev0",
|
118 |
+
"vision_config": {
|
119 |
+
"_name_or_path": "",
|
120 |
+
"add_cross_attention": false,
|
121 |
+
"architectures": null,
|
122 |
+
"attention_heads": 16,
|
123 |
+
"bad_words_ids": null,
|
124 |
+
"begin_suppress_tokens": null,
|
125 |
+
"bos_token_id": null,
|
126 |
+
"chunk_size_feed_forward": 0,
|
127 |
+
"cross_attention_hidden_size": null,
|
128 |
+
"decoder_start_token_id": null,
|
129 |
+
"diversity_penalty": 0.0,
|
130 |
+
"do_sample": false,
|
131 |
+
"early_stopping": false,
|
132 |
+
"encoder_no_repeat_ngram_size": 0,
|
133 |
+
"eos_token_id": null,
|
134 |
+
"exponential_decay_length_penalty": null,
|
135 |
+
"finetuning_task": null,
|
136 |
+
"forced_bos_token_id": null,
|
137 |
+
"forced_eos_token_id": null,
|
138 |
+
"hidden_act": "gelu",
|
139 |
+
"hidden_size": 1280,
|
140 |
+
"id2label": {
|
141 |
+
"0": "LABEL_0",
|
142 |
+
"1": "LABEL_1"
|
143 |
+
},
|
144 |
+
"image_size": 560,
|
145 |
+
"intermediate_layers_indices": [
|
146 |
+
3,
|
147 |
+
7,
|
148 |
+
15,
|
149 |
+
23,
|
150 |
+
30
|
151 |
+
],
|
152 |
+
"intermediate_size": 5120,
|
153 |
+
"is_decoder": false,
|
154 |
+
"is_encoder_decoder": false,
|
155 |
+
"label2id": {
|
156 |
+
"LABEL_0": 0,
|
157 |
+
"LABEL_1": 1
|
158 |
+
},
|
159 |
+
"length_penalty": 1.0,
|
160 |
+
"max_length": 20,
|
161 |
+
"max_num_tiles": 4,
|
162 |
+
"min_length": 0,
|
163 |
+
"model_type": "mllama_vision_model",
|
164 |
+
"no_repeat_ngram_size": 0,
|
165 |
+
"norm_eps": 1e-05,
|
166 |
+
"num_beam_groups": 1,
|
167 |
+
"num_beams": 1,
|
168 |
+
"num_channels": 3,
|
169 |
+
"num_global_layers": 8,
|
170 |
+
"num_hidden_layers": 32,
|
171 |
+
"num_return_sequences": 1,
|
172 |
+
"output_attentions": false,
|
173 |
+
"output_hidden_states": false,
|
174 |
+
"output_scores": false,
|
175 |
+
"pad_token_id": null,
|
176 |
+
"patch_size": 14,
|
177 |
+
"prefix": null,
|
178 |
+
"problem_type": null,
|
179 |
+
"pruned_heads": {},
|
180 |
+
"remove_invalid_values": false,
|
181 |
+
"repetition_penalty": 1.0,
|
182 |
+
"return_dict": true,
|
183 |
+
"return_dict_in_generate": false,
|
184 |
+
"sep_token_id": null,
|
185 |
+
"supported_aspect_ratios": [
|
186 |
+
[
|
187 |
+
1,
|
188 |
+
1
|
189 |
+
],
|
190 |
+
[
|
191 |
+
1,
|
192 |
+
2
|
193 |
+
],
|
194 |
+
[
|
195 |
+
1,
|
196 |
+
3
|
197 |
+
],
|
198 |
+
[
|
199 |
+
1,
|
200 |
+
4
|
201 |
+
],
|
202 |
+
[
|
203 |
+
2,
|
204 |
+
1
|
205 |
+
],
|
206 |
+
[
|
207 |
+
2,
|
208 |
+
2
|
209 |
+
],
|
210 |
+
[
|
211 |
+
3,
|
212 |
+
1
|
213 |
+
],
|
214 |
+
[
|
215 |
+
4,
|
216 |
+
1
|
217 |
+
]
|
218 |
+
],
|
219 |
+
"suppress_tokens": null,
|
220 |
+
"task_specific_params": null,
|
221 |
+
"temperature": 1.0,
|
222 |
+
"tf_legacy_loss": false,
|
223 |
+
"tie_encoder_decoder": false,
|
224 |
+
"tie_word_embeddings": true,
|
225 |
+
"tokenizer_class": null,
|
226 |
+
"top_k": 50,
|
227 |
+
"top_p": 1.0,
|
228 |
+
"torch_dtype": "bfloat16",
|
229 |
+
"torchscript": false,
|
230 |
+
"typical_p": 1.0,
|
231 |
+
"use_bfloat16": false,
|
232 |
+
"vision_output_dim": 7680
|
233 |
+
}
|
234 |
+
}
|
generation_config.json
ADDED
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"bos_token_id": 128000,
|
3 |
+
"do_sample": true,
|
4 |
+
"eos_token_id": [
|
5 |
+
128001,
|
6 |
+
128008,
|
7 |
+
128009
|
8 |
+
],
|
9 |
+
"pad_token_id": 128004,
|
10 |
+
"temperature": 0.6,
|
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|
1 |
+
{
|
2 |
+
"added_tokens_decoder": {
|
3 |
+
"128000": {
|
4 |
+
"content": "<|begin_of_text|>",
|
5 |
+
"lstrip": false,
|
6 |
+
"normalized": false,
|
7 |
+
"rstrip": false,
|
8 |
+
"single_word": false,
|
9 |
+
"special": true
|
10 |
+
},
|
11 |
+
"128001": {
|
12 |
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"content": "<|end_of_text|>",
|
13 |
+
"lstrip": false,
|
14 |
+
"normalized": false,
|
15 |
+
"rstrip": false,
|
16 |
+
"single_word": false,
|
17 |
+
"special": true
|
18 |
+
},
|
19 |
+
"128002": {
|
20 |
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"content": "<|reserved_special_token_0|>",
|
21 |
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"lstrip": false,
|
22 |
+
"normalized": false,
|
23 |
+
"rstrip": false,
|
24 |
+
"single_word": false,
|
25 |
+
"special": true
|
26 |
+
},
|
27 |
+
"128003": {
|
28 |
+
"content": "<|reserved_special_token_1|>",
|
29 |
+
"lstrip": false,
|
30 |
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"normalized": false,
|
31 |
+
"rstrip": false,
|
32 |
+
"single_word": false,
|
33 |
+
"special": true
|
34 |
+
},
|
35 |
+
"128004": {
|
36 |
+
"content": "<|finetune_right_pad_id|>",
|
37 |
+
"lstrip": false,
|
38 |
+
"normalized": false,
|
39 |
+
"rstrip": false,
|
40 |
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"single_word": false,
|
41 |
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"special": true
|
42 |
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},
|
43 |
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"128005": {
|
44 |
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"content": "<|step_id|>",
|
45 |
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|
46 |
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"normalized": false,
|
47 |
+
"rstrip": false,
|
48 |
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|
49 |
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"special": true
|
50 |
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|
51 |
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"128006": {
|
52 |
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"content": "<|start_header_id|>",
|
53 |
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|
54 |
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|
55 |
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|
56 |
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|
57 |
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"special": true
|
58 |
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},
|
59 |
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"128007": {
|
60 |
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"content": "<|end_header_id|>",
|
61 |
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|
62 |
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|
63 |
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|
64 |
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|
65 |
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|
66 |
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},
|
67 |
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"128008": {
|
68 |
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"content": "<|eom_id|>",
|
69 |
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|
70 |
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|
71 |
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|
72 |
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73 |
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|
74 |
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|
75 |
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|
76 |
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|
77 |
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|
78 |
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|
79 |
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|
80 |
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|
81 |
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|
82 |
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|
83 |
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|
84 |
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"content": "<|python_tag|>",
|
85 |
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|
86 |
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|
87 |
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|
88 |
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|
89 |
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|
90 |
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|
91 |
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|
92 |
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|
93 |
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|
94 |
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|
95 |
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|
96 |
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|
97 |
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|
98 |
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},
|
99 |
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"128012": {
|
100 |
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"content": "<|reserved_special_token_3|>",
|
101 |
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|
102 |
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|
103 |
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|
104 |
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|
105 |
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|
106 |
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},
|
107 |
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|
108 |
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"content": "<|reserved_special_token_4|>",
|
109 |
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|
110 |
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|
111 |
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|
112 |
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|
113 |
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|
114 |
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},
|
115 |
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|
116 |
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"content": "<|reserved_special_token_5|>",
|
117 |
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|
118 |
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|
119 |
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|
120 |
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|
121 |
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|
122 |
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|
123 |
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|
124 |
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"content": "<|reserved_special_token_6|>",
|
125 |
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|
126 |
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|
127 |
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|
128 |
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|
129 |
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|
130 |
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|
131 |
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|
132 |
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|
133 |
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|
134 |
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|
135 |
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|
136 |
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|
137 |
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|
138 |
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|
139 |
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|
140 |
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|
141 |
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|
142 |
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|
143 |
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|
144 |
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|
145 |
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|
146 |
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},
|
147 |
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"128018": {
|
148 |
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"content": "<|reserved_special_token_9|>",
|
149 |
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|
150 |
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|
151 |
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|
152 |
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|
153 |
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|
154 |
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|
155 |
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|
156 |
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"content": "<|reserved_special_token_10|>",
|
157 |
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|
158 |
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|
159 |
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|
160 |
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|
161 |
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|
162 |
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|
163 |
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|
164 |
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|
165 |
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|
166 |
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|
167 |
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|
168 |
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|
169 |
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|
170 |
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},
|
171 |
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|
172 |
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"content": "<|reserved_special_token_12|>",
|
173 |
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|
174 |
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|
175 |
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|
176 |
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|
177 |
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|
178 |
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|
179 |
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|
180 |
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"content": "<|reserved_special_token_13|>",
|
181 |
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|
182 |
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|
183 |
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|
184 |
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|
185 |
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|
186 |
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|
187 |
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|
188 |
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"content": "<|reserved_special_token_14|>",
|
189 |
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|
190 |
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|
191 |
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|
192 |
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|
193 |
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|
194 |
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},
|
195 |
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|
196 |
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"content": "<|reserved_special_token_15|>",
|
197 |
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|
198 |
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|
199 |
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|
200 |
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|
201 |
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|
202 |
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},
|
203 |
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|
204 |
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"content": "<|reserved_special_token_16|>",
|
205 |
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|
206 |
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|
207 |
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|
208 |
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|
209 |
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|
210 |
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},
|
211 |
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"128026": {
|
212 |
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"content": "<|reserved_special_token_17|>",
|
213 |
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|
214 |
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|
215 |
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|
216 |
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|
217 |
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|
218 |
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|
219 |
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"128027": {
|
220 |
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"content": "<|reserved_special_token_18|>",
|
221 |
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|
222 |
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|
223 |
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|
224 |
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|
225 |
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|
226 |
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|
227 |
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"128028": {
|
228 |
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"content": "<|reserved_special_token_19|>",
|
229 |
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"lstrip": false,
|
230 |
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"normalized": false,
|
231 |
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|
232 |
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|
233 |
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|
234 |
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},
|
235 |
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|
236 |
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"content": "<|reserved_special_token_20|>",
|
237 |
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|
238 |
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|
239 |
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|
240 |
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|
241 |
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|
242 |
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|
243 |
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|
244 |
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|
245 |
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|
246 |
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|
247 |
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248 |
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|
249 |
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|
250 |
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|
251 |
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|
252 |
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|
253 |
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|
254 |
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|
255 |
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|
256 |
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|
257 |
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|
258 |
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|
259 |
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|
260 |
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"content": "<|reserved_special_token_23|>",
|
261 |
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|
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2006 |
+
"normalized": false,
|
2007 |
+
"rstrip": false,
|
2008 |
+
"single_word": false,
|
2009 |
+
"special": true
|
2010 |
+
},
|
2011 |
+
"128251": {
|
2012 |
+
"content": "<|reserved_special_token_242|>",
|
2013 |
+
"lstrip": false,
|
2014 |
+
"normalized": false,
|
2015 |
+
"rstrip": false,
|
2016 |
+
"single_word": false,
|
2017 |
+
"special": true
|
2018 |
+
},
|
2019 |
+
"128252": {
|
2020 |
+
"content": "<|reserved_special_token_243|>",
|
2021 |
+
"lstrip": false,
|
2022 |
+
"normalized": false,
|
2023 |
+
"rstrip": false,
|
2024 |
+
"single_word": false,
|
2025 |
+
"special": true
|
2026 |
+
},
|
2027 |
+
"128253": {
|
2028 |
+
"content": "<|reserved_special_token_244|>",
|
2029 |
+
"lstrip": false,
|
2030 |
+
"normalized": false,
|
2031 |
+
"rstrip": false,
|
2032 |
+
"single_word": false,
|
2033 |
+
"special": true
|
2034 |
+
},
|
2035 |
+
"128254": {
|
2036 |
+
"content": "<|reserved_special_token_245|>",
|
2037 |
+
"lstrip": false,
|
2038 |
+
"normalized": false,
|
2039 |
+
"rstrip": false,
|
2040 |
+
"single_word": false,
|
2041 |
+
"special": true
|
2042 |
+
},
|
2043 |
+
"128255": {
|
2044 |
+
"content": "<|reserved_special_token_246|>",
|
2045 |
+
"lstrip": false,
|
2046 |
+
"normalized": false,
|
2047 |
+
"rstrip": false,
|
2048 |
+
"single_word": false,
|
2049 |
+
"special": true
|
2050 |
+
},
|
2051 |
+
"128256": {
|
2052 |
+
"content": "<|image|>",
|
2053 |
+
"lstrip": false,
|
2054 |
+
"normalized": false,
|
2055 |
+
"rstrip": false,
|
2056 |
+
"single_word": false,
|
2057 |
+
"special": true
|
2058 |
+
}
|
2059 |
+
},
|
2060 |
+
"bos_token": "<|begin_of_text|>",
|
2061 |
+
"chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- if strftime_now is defined %}\n {%- set date_string = strftime_now(\"%d %b %Y\") %}\n {%- else %}\n {%- set date_string = \"26 Jul 2024\" %}\n {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- Find out if there are any images #}\n{% set image_ns = namespace(has_images=false) %} \n{%- for message in messages %}\n {%- for content in message['content'] %}\n {%- if content['type'] == 'image' %}\n {%- set image_ns.has_images = true %}\n {%- endif %}\n {%- endfor %}\n{%- endfor %}\n\n{#- Error out if there are images and system message #}\n{%- if image_ns.has_images and not system_message == \"\" %}\n {{- raise_exception(\"Prompting with images is incompatible with system messages.\") }}\n{%- endif %}\n\n{#- System message if there are no images #}\n{%- if not image_ns.has_images %}\n {{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n {%- if tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n {%- endif %}\n {{- \"Cutting Knowledge Date: December 2023\\n\" }}\n {{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n {%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {%- endif %}\n {{- system_message }}\n {{- \"<|eot_id|>\" }}\n{%- endif %}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n' }}\n {%- if message['content'] is string %}\n {{- message['content'] }}\n {%- else %}\n {%- for content in message['content'] %}\n {%- if content['type'] == 'image' %}\n {{- '<|image|>' }}\n {%- elif content['type'] == 'text' %}\n {{- content['text'] }}\n {%- endif %}\n {%- endfor %}\n {%- endif %}\n {{- '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {{- \"<|eot_id|>\" }}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
|
2062 |
+
"clean_up_tokenization_spaces": true,
|
2063 |
+
"eos_token": "<|eot_id|>",
|
2064 |
+
"model_input_names": [
|
2065 |
+
"input_ids",
|
2066 |
+
"attention_mask"
|
2067 |
+
],
|
2068 |
+
"model_max_length": 131072,
|
2069 |
+
"pad_token": "<|finetune_right_pad_id|>",
|
2070 |
+
"processor_class": "MllamaProcessor",
|
2071 |
+
"tokenizer_class": "PreTrainedTokenizerFast"
|
2072 |
+
}
|