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--- |
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base_model: unsloth/meta-llama-3.1-8b-instruct-bnb-4bit |
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language: |
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- en |
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license: llama3.1 |
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tags: |
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- text-generation-inference |
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- transformers |
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- unsloth |
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- llama |
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- trl |
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- sft |
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- reflection |
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datasets: |
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- mahiatlinux/Reflection-Dataset-v2 |
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--- |
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# Uploaded model |
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- **Developed by:** Solshine (Caleb DeLeeuw) |
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- **License:** LLama 3.1 License |
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- **Finetuned from model :** unsloth/meta-llama-3.1-8b-instruct-bnb-4bit |
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Inspired by and featuring the Reflection Tuning technique pioneered by Matt Shumer (possibly earlier innovated by the team at Anthropic.) |
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*To the authors' knowledge, this is the first "reflection tuned" Llama 3.1 8B LLM* |
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**As per the inspiring model "mattshumer/Reflection-Llama-3.1-70B" (this mode was not used in the training process nor as a foundational model, but only served as inspiration) :** |
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''' |
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During sampling, the model will start by outputting reasoning inside <thinking> and </thinking> tags, and then once it is satisfied with its reasoning, it will output the final answer inside <output> and </output> tags. Each of these tags are special tokens, trained into the model. |
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This enables the model to separate its internal thoughts and reasoning from its final answer, improving the experience for the user. |
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Inside the <thinking> section, the model may output one or more <reflection> tags, which signals the model has caught an error in its reasoning and will attempt to correct it before providing a final answer. |
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System Prompt: |
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The system prompt used for training this model is: |
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You are a world-class AI system, capable of complex reasoning and reflection. Reason through the query inside <thinking> tags, and then provide your final response inside <output> tags. If you detect that you made a mistake in your reasoning at any point, correct yourself inside <reflection> tags. |
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We recommend using this exact system prompt to get the best results from Reflection Llama-3.1 70B. You may also want to experiment combining this system prompt with your own custom instructions to customize the behavior of the model. |
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Chat Format: |
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As mentioned above, the model uses the standard Llama 3.1 chat format. Here’s an example: |
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<|begin_of_text|><|start_header_id|>system<|end_header_id|> |
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You are a world-class AI system, capable of complex reasoning and reflection. Reason through the query inside <thinking> tags, and then provide your final response inside <output> tags. If you detect that you made a mistake in your reasoning at any point, correct yourself inside <reflection> tags.<|eot_id|><|start_header_id|>user<|end_header_id|> |
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what is 2+2?<|eot_id|><|start_header_id|>assistant<|end_header_id|> |
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''' |
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This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. |
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
