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--- |
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tags: |
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- autotrain |
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- text-generation |
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widget: |
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- text: 'I love AutoTrain because ' |
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license: openrail |
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language: |
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- en |
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metrics: |
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- accuracy |
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pipeline_tag: text-generation |
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--- |
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# Model Trained Using AutoTrain |
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``` |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_path = "Andyrasika/mistral_autotrain_llm" |
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tokenizer = AutoTokenizer.from_pretrained(model_path) |
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model = AutoModelForCausalLM.from_pretrained(model_path) |
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``` |
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``` |
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input_text = "Health benefits of regular exercise" |
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input_ids = tokenizer.encode(input_text, return_tensors="pt") |
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output = model.generate(input_ids) |
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predicted_text = tokenizer.decode(output[0], skip_special_tokens=False) |
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print(predicted_text) |
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``` |
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Output: |
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``` |
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Health benefits of regular exercise include improved cardiovascular health, increased strength and flexibility, improved mental |
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``` |
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Resources: |
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- https://github.com/huggingface/autotrain-advanced/issues/339 |
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- https://www.kdnuggets.com/how-to-use-hugging-face-autotrain-to-finetune-llms |
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- https://github.com/hiyouga/LLaMA-Factory#llama-factory-training-and-evaluating-large-language-models-with-minimal-effort |
