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README.md

@@ -1,13 +1,173 @@
 ---
+extra_gated_heading: You need to share contact information with Meta to access this
+  model
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+  \ will be governed and  construed under the laws of the State of California without\
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+  \  USE POLICY ### Llama 2 Acceptable Use Policy Meta is committed to promoting safe\
+  \ and fair use of its tools and features, including Llama 2. If you access or use\
+  \ Llama 2, you agree to this Acceptable Use Policy (“Policy”). The most recent copy\
+  \ of this policy can be found at [ai.meta.com/llama/use-policy](http://ai.meta.com/llama/use-policy).\
+  \ #### Prohibited Uses We want everyone to use Llama 2 safely and responsibly. You\
+  \ agree you will not use, or allow others to use, Llama 2 to:  1. Violate the law\
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+  \ any third-party rights, including the outputs or results of any products or services\
+  \ using the Llama 2 Materials\n  7. Create, generate, or facilitate the creation\
+  \ of malicious code, malware, computer viruses or do anything else that could disable,\
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+  \ or appearance of a website or computer system \n2. 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 2 related\
+  \ to the following:\n  1. Military, warfare, nuclear industries or applications,\
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+  \ Traffic Arms Regulations (ITAR) maintained by the United States Department of\
+  \ State\n  2. Guns and illegal weapons (including weapon development)\n  3. Illegal\
+  \ drugs and regulated/controlled substances\n  4. Operation of critical infrastructure,\
+  \ transportation technologies, or heavy machinery\n  5. Self-harm or harm to others,\
+  \ including suicide, cutting, and eating disorders\n  6. Any content intended to\
+  \ incite or promote violence, abuse, or any infliction of bodily harm to an individual\n\
+  3. Intentionally deceive or mislead others, including use of Llama 2 related to\
+  \ the following:\n  1. Generating, promoting, or furthering fraud or the creation\
+  \ or promotion of disinformation\n  2. Generating, promoting, or furthering defamatory\
+  \ content, including the creation of defamatory statements, images, or other content\n\
+  \  3. Generating, promoting, or further distributing spam\n  4. Impersonating another\
+  \ individual without consent, authorization, or legal right\n  5. Representing that\
+  \ the use of Llama 2 or outputs are human-generated\n  6. Generating or facilitating\
+  \ false online engagement, including fake reviews and other means of fake online\
+  \ engagement \n  4. Fail to appropriately disclose to end users any known dangers\
+  \ of your AI system \nPlease 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: * Reporting issues with the model: [github.com/facebookresearch/llama](http://github.com/facebookresearch/llama)\
+  \ * Reporting risky content generated by the model: [developers.facebook.com/llama_output_feedback](http://developers.facebook.com/llama_output_feedback)\
+  \ * Reporting bugs and security concerns: [facebook.com/whitehat/info](http://facebook.com/whitehat/info)\
+  \ * Reporting violations of the Acceptable Use Policy or unlicensed uses of Llama:\
+  \ [[email protected]](mailto:[email protected])"
+extra_gated_fields:
+  First Name: text
+  Last Name: text
+  Date of birth: date_picker
+  Country: country
+  Affiliation: text
+  geo: ip_location
+  ? By clicking Submit below I accept the terms of the license and acknowledge that
+    the information I provide will be collected stored processed and shared in accordance
+    with the Meta Privacy Policy
+  : checkbox
+extra_gated_description: The information you provide will be collected, stored, processed
+  and shared in accordance with the [Meta Privacy Policy](https://www.facebook.com/privacy/policy/).
+extra_gated_button_content: Submit
 language:
 - code
 pipeline_tag: text-generation
 tags:
+- facebook
+- meta
+- pytorch
+- llama
 - llama-2
 - TensorBlock
 - GGUF
 license: llama2
-base_model: codellama/CodeLlama-7b-Python-hf
+base_model: meta-llama/CodeLlama-7b-Python-hf
 ---
 
 <div style="width: auto; margin-left: auto; margin-right: auto">
@@ -21,12 +181,11 @@ base_model: codellama/CodeLlama-7b-Python-hf
     </div>
 </div>
 
-## codellama/CodeLlama-7b-Python-hf - GGUF
+## meta-llama/CodeLlama-7b-Python-hf - GGUF
 
-This repo contains GGUF format model files for [codellama/CodeLlama-7b-Python-hf](https://huggingface.co/codellama/CodeLlama-7b-Python-hf).
-
-The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
+This repo contains GGUF format model files for [meta-llama/CodeLlama-7b-Python-hf](https://huggingface.co/meta-llama/CodeLlama-7b-Python-hf).
 
+The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
 
 <div style="text-align: left; margin: 20px 0;">
     <a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
@@ -36,7 +195,6 @@ The files were quantized using machines provided by [TensorBlock](https://tensor
 
 ## Prompt template
 
-
 ```
 
 ```
@@ -45,18 +203,18 @@ The files were quantized using machines provided by [TensorBlock](https://tensor
 
 | Filename | Quant type | File Size | Description |
 | -------- | ---------- | --------- | ----------- |
-| [CodeLlama-7b-Python-hf-Q2_K.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q2_K.gguf) | Q2_K | 2.359 GB | smallest, significant quality loss - not recommended for most purposes |
-| [CodeLlama-7b-Python-hf-Q3_K_S.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q3_K_S.gguf) | Q3_K_S | 2.746 GB | very small, high quality loss |
-| [CodeLlama-7b-Python-hf-Q3_K_M.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q3_K_M.gguf) | Q3_K_M | 3.072 GB | very small, high quality loss |
-| [CodeLlama-7b-Python-hf-Q3_K_L.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q3_K_L.gguf) | Q3_K_L | 3.350 GB | small, substantial quality loss |
-| [CodeLlama-7b-Python-hf-Q4_0.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q4_0.gguf) | Q4_0 | 3.563 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
-| [CodeLlama-7b-Python-hf-Q4_K_S.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q4_K_S.gguf) | Q4_K_S | 3.592 GB | small, greater quality loss |
-| [CodeLlama-7b-Python-hf-Q4_K_M.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q4_K_M.gguf) | Q4_K_M | 3.801 GB | medium, balanced quality - recommended |
-| [CodeLlama-7b-Python-hf-Q5_0.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q5_0.gguf) | Q5_0 | 4.332 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
-| [CodeLlama-7b-Python-hf-Q5_K_S.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q5_K_S.gguf) | Q5_K_S | 4.332 GB | large, low quality loss - recommended |
-| [CodeLlama-7b-Python-hf-Q5_K_M.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q5_K_M.gguf) | Q5_K_M | 4.455 GB | large, very low quality loss - recommended |
-| [CodeLlama-7b-Python-hf-Q6_K.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q6_K.gguf) | Q6_K | 5.149 GB | very large, extremely low quality loss |
-| [CodeLlama-7b-Python-hf-Q8_0.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q8_0.gguf) | Q8_0 | 6.669 GB | very large, extremely low quality loss - not recommended |
+| [CodeLlama-7b-Python-hf-Q2_K.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q2_K.gguf) | Q2_K | 2.533 GB | smallest, significant quality loss - not recommended for most purposes |
+| [CodeLlama-7b-Python-hf-Q3_K_S.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q3_K_S.gguf) | Q3_K_S | 2.948 GB | very small, high quality loss |
+| [CodeLlama-7b-Python-hf-Q3_K_M.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q3_K_M.gguf) | Q3_K_M | 3.298 GB | very small, high quality loss |
+| [CodeLlama-7b-Python-hf-Q3_K_L.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q3_K_L.gguf) | Q3_K_L | 3.597 GB | small, substantial quality loss |
+| [CodeLlama-7b-Python-hf-Q4_0.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q4_0.gguf) | Q4_0 | 3.826 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [CodeLlama-7b-Python-hf-Q4_K_S.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q4_K_S.gguf) | Q4_K_S | 3.857 GB | small, greater quality loss |
+| [CodeLlama-7b-Python-hf-Q4_K_M.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q4_K_M.gguf) | Q4_K_M | 4.081 GB | medium, balanced quality - recommended |
+| [CodeLlama-7b-Python-hf-Q5_0.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q5_0.gguf) | Q5_0 | 4.652 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [CodeLlama-7b-Python-hf-Q5_K_S.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q5_K_S.gguf) | Q5_K_S | 4.652 GB | large, low quality loss - recommended |
+| [CodeLlama-7b-Python-hf-Q5_K_M.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q5_K_M.gguf) | Q5_K_M | 4.783 GB | large, very low quality loss - recommended |
+| [CodeLlama-7b-Python-hf-Q6_K.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q6_K.gguf) | Q6_K | 5.529 GB | very large, extremely low quality loss |
+| [CodeLlama-7b-Python-hf-Q8_0.gguf](https://huggingface.co/tensorblock/CodeLlama-7b-Python-hf-GGUF/blob/main/CodeLlama-7b-Python-hf-Q8_0.gguf) | Q8_0 | 7.161 GB | very large, extremely low quality loss - not recommended |
 
 
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