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--- |
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base_model: unsloth/DeepSeek-R1-Distill-Qwen-14B |
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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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- trl |
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license: apache-2.0 |
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language: |
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- en |
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--- |
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# Disclaimer!! |
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Hello! This model is not perfect yet, I am just experimenting! |
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This is me attempting the [AIMO Prize 2 Kaggle contest](https://www.kaggle.com/competitions/ai-mathematical-olympiad-progress-prize-2) |
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I have decided to release the models before the competition ends because I don't care about winning the contest as much! |
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My research fields are Medical Computing and Reinforcement Learning. Feel free to add me on [LinkedIn](https://www.linkedin.com/in/sindhusatish/) if you want to chat! |
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- **Developed by:** sindhusatish97 |
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- **License:** apache-2.0 |
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- **Finetuned from model :** unsloth/DeepSeek-R1-Distill-Qwen-14B |
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This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. - Huge thanks to the awesome team for releasing these distilled models! |
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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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# Test it out! |
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```python |
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!pip install unsloth |
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# Also get the latest nightly Unsloth! |
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!pip install --force-reinstall --no-cache-dir --no-deps git+https://github.com/unslothai/unsloth.git |
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from unsloth import FastLanguageModel |
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import torch |
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max_seq_length = 5120 # I chose this value based on Qwen's max sequence length. |
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dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+ |
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load_in_4bit = True |
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model, tokenizer = FastLanguageModel.from_pretrained( |
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model_name = "sindhusatish97/DeepSeek-R1-Distill-Qwen-14B-unsloth-bnb-4bit-AIMO_CoT", |
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max_seq_length = max_seq_length, |
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dtype = dtype, |
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load_in_4bit = load_in_4bit, |
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# token = "hf_...", # use one if using gated models like meta-llama/Llama-2-7b-hf |
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) |
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FastLanguageModel.for_inference(model) |
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inputs = tokenizer( |
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[ |
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"""4 pints of a 5% antifreeze solution and 8 pints of a 20% antifreeze solution must be mixed to obtain 12 pints of a |
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solution with what percentage of antifreeze?""" |
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], return_tensors = "pt").to("cuda") |
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from transformers import TextStreamer |
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text_streamer = TextStreamer(tokenizer) |
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_ = model.generate(**inputs, streamer = text_streamer, max_length = 2048) |
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``` |
