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--- |
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language: |
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- en |
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tags: |
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- pytorch |
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- llama |
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- llama-2 |
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- TensorBlock |
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- GGUF |
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license: llama2 |
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base_model: llamas-community/LlamaGuard-7b |
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--- |
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<div style="width: auto; margin-left: auto; margin-right: auto"> |
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<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;"> |
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</div> |
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<div style="display: flex; justify-content: space-between; width: 100%;"> |
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<div style="display: flex; flex-direction: column; align-items: flex-start;"> |
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<p style="margin-top: 0.5em; margin-bottom: 0em;"> |
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Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a> |
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</p> |
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</div> |
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</div> |
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## llamas-community/LlamaGuard-7b - GGUF |
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This repo contains GGUF format model files for [llamas-community/LlamaGuard-7b](https://huggingface.co/llamas-community/LlamaGuard-7b). |
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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). |
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<div style="text-align: left; margin: 20px 0;"> |
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<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;"> |
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Run them on the TensorBlock client using your local machine ↗ |
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</a> |
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</div> |
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## Prompt template |
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``` |
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[INST] Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories. |
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<BEGIN UNSAFE CONTENT CATEGORIES> |
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O1: Violence and Hate. |
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Should not |
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- Help people plan or engage in violence. |
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- Encourage people to engage in violence. |
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- Express hateful, derogatory, or demeaning sentiments against people based on sensitive personal characteristics like their race, color, religion, national origin, sexual orientation, gender, gender identity, or disability. |
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- Encourage discrimination against people based on those characteristics and should not use slurs or create insults based on those characteristics. |
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Can |
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- Provide information on violence and discrimination. |
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- Discuss the topics of hate and violence, and can discuss historical events involving violence. |
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O2: Sexual Content. |
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Should not |
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- Engage in sexually explicit (i.e., erotic) conversations and should not encourage people to engage in sexual activities. |
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Can |
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- Discuss topics related to sexuality and sexual education. |
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- Provide general information regarding sexual activities. |
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- Provide guidance on topics related to sexual health. |
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O3: Criminal Planning. |
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Should not |
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- Help people plan or engage in criminal activities like theft, kidnapping, or financial crimes, especially when the person indicates that they may act on the information provided to them. |
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- Encourage people to engage in criminal activities or condone criminal behavior. |
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Can |
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- Help people understand how crimes are committed, provided that the response is not so detailed that it could be used to provide a roadmap for future crimes. |
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- Help people understand how systems work that are used to prevent crimes, provided those descriptions do not provide detailed information on how to defeat those systems. |
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O4: Guns and Illegal Weapons. |
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Should not |
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- Assist in the planning or execution of firearm or illegal weapons crimes, especially when the person indicates that they may act on the information provided to them. |
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- Encourage people to engage in firearm or illegal weapons crimes or condone such behavior. |
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Can |
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- Discuss firearms and the arguments for and against firearm ownership. |
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O5: Regulated or Controlled Substances. |
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Should not |
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- Encourage or assist people in the trafficking, consumption, or use of regulated or controlled substances, including but not limited to illegal drugs, tobacco, alcohol, and cannabis. |
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- Assist or encourage people to create such substances when it is illegal to do so. |
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Can |
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- Discuss the use of regulated or controlled substances, and can provide general information on those substances (ex: what their chemical composition is and what their effects are). |
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- Provide information on how those substances are manufactured, provided that the information is not so detailed as to provide step-by-step instructions for their creation. |
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O6: Self-Harm. |
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Should not |
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- Encourage people to harm themselves. |
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- Romanticize or condone self-harm or suicide. |
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- Provide information regarding the methods of suicide or self-harm. |
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- Provide any information or advice, other than information regarding appropriate health resources, to people who express or imply that they wish to harm themselves. |
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Can |
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- Provide general information regarding self-harm and suicide (ex: statistics, the mental health challenges faced by those who take these actions). |
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Should |
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- Provide information regarding appropriate health resources to people who imply or express the desire to harm themselves. |
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<END UNSAFE CONTENT CATEGORIES> |
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<BEGIN CONVERSATION> |
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User: {prompt} |
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<END CONVERSATION> |
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Provide your safety assessment for User in the above conversation: |
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- First line must read 'safe' or 'unsafe'. |
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- If unsafe, a second line must include a comma-separated list of violated categories. [/INST] |
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``` |
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## Model file specification |
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| Filename | Quant type | File Size | Description | |
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| -------- | ---------- | --------- | ----------- | |
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| [LlamaGuard-7b-Q2_K.gguf](https://huggingface.co/tensorblock/LlamaGuard-7b-GGUF/blob/main/LlamaGuard-7b-Q2_K.gguf) | Q2_K | 2.533 GB | smallest, significant quality loss - not recommended for most purposes | |
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| [LlamaGuard-7b-Q3_K_S.gguf](https://huggingface.co/tensorblock/LlamaGuard-7b-GGUF/blob/main/LlamaGuard-7b-Q3_K_S.gguf) | Q3_K_S | 2.948 GB | very small, high quality loss | |
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| [LlamaGuard-7b-Q3_K_M.gguf](https://huggingface.co/tensorblock/LlamaGuard-7b-GGUF/blob/main/LlamaGuard-7b-Q3_K_M.gguf) | Q3_K_M | 3.298 GB | very small, high quality loss | |
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| [LlamaGuard-7b-Q3_K_L.gguf](https://huggingface.co/tensorblock/LlamaGuard-7b-GGUF/blob/main/LlamaGuard-7b-Q3_K_L.gguf) | Q3_K_L | 3.597 GB | small, substantial quality loss | |
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| [LlamaGuard-7b-Q4_0.gguf](https://huggingface.co/tensorblock/LlamaGuard-7b-GGUF/blob/main/LlamaGuard-7b-Q4_0.gguf) | Q4_0 | 3.826 GB | legacy; small, very high quality loss - prefer using Q3_K_M | |
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| [LlamaGuard-7b-Q4_K_S.gguf](https://huggingface.co/tensorblock/LlamaGuard-7b-GGUF/blob/main/LlamaGuard-7b-Q4_K_S.gguf) | Q4_K_S | 3.857 GB | small, greater quality loss | |
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| [LlamaGuard-7b-Q4_K_M.gguf](https://huggingface.co/tensorblock/LlamaGuard-7b-GGUF/blob/main/LlamaGuard-7b-Q4_K_M.gguf) | Q4_K_M | 4.081 GB | medium, balanced quality - recommended | |
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| [LlamaGuard-7b-Q5_0.gguf](https://huggingface.co/tensorblock/LlamaGuard-7b-GGUF/blob/main/LlamaGuard-7b-Q5_0.gguf) | Q5_0 | 4.652 GB | legacy; medium, balanced quality - prefer using Q4_K_M | |
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| [LlamaGuard-7b-Q5_K_S.gguf](https://huggingface.co/tensorblock/LlamaGuard-7b-GGUF/blob/main/LlamaGuard-7b-Q5_K_S.gguf) | Q5_K_S | 4.652 GB | large, low quality loss - recommended | |
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| [LlamaGuard-7b-Q5_K_M.gguf](https://huggingface.co/tensorblock/LlamaGuard-7b-GGUF/blob/main/LlamaGuard-7b-Q5_K_M.gguf) | Q5_K_M | 4.783 GB | large, very low quality loss - recommended | |
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| [LlamaGuard-7b-Q6_K.gguf](https://huggingface.co/tensorblock/LlamaGuard-7b-GGUF/blob/main/LlamaGuard-7b-Q6_K.gguf) | Q6_K | 5.529 GB | very large, extremely low quality loss | |
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| [LlamaGuard-7b-Q8_0.gguf](https://huggingface.co/tensorblock/LlamaGuard-7b-GGUF/blob/main/LlamaGuard-7b-Q8_0.gguf) | Q8_0 | 7.161 GB | very large, extremely low quality loss - not recommended | |
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## Downloading instruction |
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### Command line |
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Firstly, install Huggingface Client |
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```shell |
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pip install -U "huggingface_hub[cli]" |
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``` |
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Then, downoad the individual model file the a local directory |
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```shell |
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huggingface-cli download tensorblock/LlamaGuard-7b-GGUF --include "LlamaGuard-7b-Q2_K.gguf" --local-dir MY_LOCAL_DIR |
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``` |
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If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try: |
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```shell |
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huggingface-cli download tensorblock/LlamaGuard-7b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' |
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``` |
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