27 lines
786 B
Python
27 lines
786 B
Python
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from transformers import AutoTokenizer, AutoModelForCausalLM, Trainer, TrainingArguments
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from datasets import load_dataset, load_from_disk
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#post training
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model_path = "./results/checkpoint-12000"
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model = AutoModelForCausalLM.from_pretrained(model_path)
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tokenizer = AutoTokenizer.from_pretrained("tinyllama/tinyllama-1.1b-chat-v1.0")
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input_text = "ae left to go to ireland and found a fairy"
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input_ids = tokenizer.encode(input_text, return_tensors='pt')
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output = model.generate(
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input_ids=tokenizer.encode(input_text, return_tensors="pt"),
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max_length=400,
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num_return_sequences=1,
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temperature=0.7,
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top_k=50,
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top_p=0.95,
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do_sample=True,
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num_beams=5
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)
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decoded_output = tokenizer.decode(output[0], skip_special_tokens=True)
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print(decoded_output)
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