Update README.md
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README.md
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@@ -22,7 +22,10 @@ tokenizer = AutoTokenizer.from_pretrained(ft)
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model = AutoModelForCausalLM.from_pretrained(ft, torch_dtype=torch.float16, low_cpu_mem_usage=True)
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model.to(device)
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prepared = tokenizer.encode(inp, return_tensors='pt').to(model.device)
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out = model.generate(input_ids=prepared, **gen_kwargs)
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generated = tokenizer.decode(out[0])
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```
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model = AutoModelForCausalLM.from_pretrained(ft, torch_dtype=torch.float16, low_cpu_mem_usage=True)
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model.to(device)
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inp = '''Sophia, 29, a student, meets a male programmer Alex from India, who is 45 <|endoftext|> alex: How was your vacation? <|endoftext|> sofie: It was amazing! I went to the beach and it felt like paradise. What about you?
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<|endoftext|> Alex: i'm good. Tell me a joke <|endoftext|> Sofie:'''
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prepared = tokenizer.encode(inp, return_tensors='pt').to(model.device)
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out = model.generate(input_ids=prepared, **gen_kwargs)
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generated = tokenizer.decode(out[0])
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```
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