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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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+
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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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+ ```
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+ # Load model directly
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+ from transformers import AutoTokenizer, AutoModelForCausalLM
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+
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+ tokenizer = AutoTokenizer.from_pretrained("heegyu/WizardVicuna-pythia-1.4b-deduped")
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+ model = AutoModelForCausalLM.from_pretrained("heegyu/WizardVicuna-pythia-1.4b-deduped")
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+
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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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+
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+ output: `['Human: Hi\n\nAssistant: Hello! How can I assist you today?<|endoftext|>']`