llama2_7b_chat_uncensored-GPTQ
Maintainer: TheBloke
65
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The llama2_7b_chat_uncensored-GPTQ model is a quantized version of George Sung's Llama2 7B Chat Uncensored model. It was created by TheBloke and provides multiple GPTQ parameter options to choose from based on your hardware and performance requirements. This contrasts with similar models like the Llama-2-7b-Chat-GPTQ which is a quantized version of Meta's Llama 2 7B Chat model.
Model inputs and outputs
The llama2_7b_chat_uncensored-GPTQ model is a text-to-text model that takes prompts as input and generates text responses. The model was fine-tuned on an uncensored conversation dataset to enable open-ended chatting without built-in alignment or safety constraints.
Inputs
- Prompts: Free-form text prompts to initiate a conversation
Outputs
- Responses: Coherent, context-aware text generated in response to the input prompt
Capabilities
The llama2_7b_chat_uncensored-GPTQ model is capable of engaging in open-ended dialogue on a wide range of topics. It can provide helpful information, generate creative ideas, and have thoughtful discussions, while avoiding harmful or biased content. However, as an uncensored model, it may also produce responses that are inappropriate or offensive.
What can I use it for?
The llama2_7b_chat_uncensored-GPTQ model could be used to power conversational AI applications, chatbots, or creative writing assistants. Developers could fine-tune or prompt the model further to specialize it for particular use cases. Potential applications include customer service, personal assistance, language learning, and creative ideation.
Things to try
Try prompting the model with open-ended questions or statements to see the range of responses it can generate. You could also experiment with different prompting techniques, such as role-playing or providing additional context, to elicit more nuanced or creative outputs. Just be mindful that as an uncensored model, the responses may contain inappropriate content.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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