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--- |
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library_name: transformers |
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license: gemma |
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language: |
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- en |
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base_model: |
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- google/gemma-2-9b-it |
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--- |
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Yippie!! It's my birthday in 2 days! So I'm gonna drop this model that I made at 2AM. |
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It's quite a bit different from what I've been doing recently, but it was pretty fun to work on. :D |
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Used a different merging technique that I quickly designed & crafted which focused on the math and logical reasoning. |
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Also fine-tuned this on Self-Play RL algorithms. |
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Not the best LLM out there but it was pretty fun making this, and coming up with something different. |
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Borrowed some ideas from my other "distillation" technique, which significantly reduces the number of layers while aiming to retain the output quality. |
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Thanks and have fun!! |
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Also happy birthday to myself :) |
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Usage (taken from official Gemma 2 9B repo): |
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```python |
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import torch |
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from transformers import pipeline |
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pipe = pipeline( |
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"text-generation", |
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model="minchyeom/birthday-llm", |
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model_kwargs={"torch_dtype": torch.bfloat16}, |
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device="cuda", # replace with "mps" to run on a Mac device |
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) |
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messages = [ |
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{"role": "user", "content": "How many r's are there in the word strawberry?"}, |
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] |
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outputs = pipe(messages, max_new_tokens=256) |
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assistant_response = outputs[0]["generated_text"][-1]["content"].strip() |
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print(assistant_response) |
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``` |
