Prajna1999
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Update README.md
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README.md
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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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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)
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