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--- |
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datasets: |
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- heegyu/wizard_vicuna_70k_v2 |
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--- |
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Hyperparameters |
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- 3 epoch |
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- 1e-4 -> 1e-5 with cosine lr decay |
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- batch size 128 |
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- max sequence length 2048 |
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- AdamW(weigth decay=0.01, b1=0.9, b2=0.99, grad_clip=1.0) |
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- no warmup |
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- BF16 |
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``` |
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# Load model directly |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("heegyu/WizardVicuna-pythia-410m-deduped") |
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model = AutoModelForCausalLM.from_pretrained("heegyu/WizardVicuna-pythia-410m-deduped") |
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inputs = tokenizer(["Human: Hi\n\nAssistant: "], return_tensors="pt") |
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outputs = model.generate(**inputs, max_new_tokens=16) |
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print(tokenizer.batch_decode(outputs, skip_special_tokens=False)) |
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``` |
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output: `['Human: Hi\n\nAssistant: Hello! How can I assist you today?<|endoftext|>']` |
