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--- |
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license: mit |
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tags: |
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- Text Generation |
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- medical |
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- GPT-neo-1.3B |
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- PyTorch |
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- LLM |
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- Finetuned |
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--- |
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LoRA +Finetuned with 50 pairs of GPT-3.5-turbo generated workout QA pair on T4 Google Collab using GPT-neo-1.3B base model. |
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Finetuned on synthetic data. |
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Collab Link https://colab.research.google.com/drive/12uv_PocrcDmvOhjPD9SGAqcXbpZAZh2a?authuser=2#scrollTo=PNcc7C51VWHV |
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# How to use the model |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("Prajna1999/Prajna-gpt-neo-1.3B-fitbot") |
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model = AutoModelForCausalLM.from_pretrained("Prajna1999/Prajna-gpt-neo-1.3B-fitbot") |
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input_ids = tokenizer.encode("Suggest some workouts for weight loss", return_tensors="pt") |
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output = model.generate(input_ids, max_length=128, |
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temperature=0, top_p=0.7, top_k=2) |
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output_text = tokenizer.decode(output[0], skip_special_tokens=True) |
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print(output_text) |
