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README.md
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---
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base_model: unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit
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tags:
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This qwen2 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)
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---
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base_model: unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit
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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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- qwen2
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- gguf
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license: apache-2.0
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language:
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- en
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datasets:
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- openai/gsm8k
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---
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This is my first reasoning model. It is fairly small and yes it still gets the answer wrong to how many r's in the word strawberry.
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You are welcome to use the model as you whish.
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In your system prompt use:
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Respond in the following format:
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<reasoning>
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...
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</reasoning>
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<answer>
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...
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</answer>
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I fine tuned the model using openai/gsm8k and to ensure costs do not go insane, I used a single A100.
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Enjoy, but please note that this model is experimental and I used it to define my pipeline.
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I will be testing fine tuning larger more capable models. I suspect they would add more value in the short term.
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---
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base_model: unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit
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tags:
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This qwen2 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)
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