fix bug at inference
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38ca429228
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fd709eacff
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@ -29,8 +29,8 @@ def main():
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return prompt
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def predict(query, history: list):
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inputs = tokenizer([format_example(query)], return_tensors="pt")
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inputs = inputs.to(model.device)
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input_ids = tokenizer([format_example(query)], return_tensors="pt")["input_ids"]
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input_ids = input_ids.to(model.device)
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gen_kwargs = {
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"do_sample": True,
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"top_p": 0.9,
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@ -41,8 +41,8 @@ def main():
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"repetition_penalty": 1.5
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}
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with torch.no_grad():
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generation_output = model.generate(**inputs, **gen_kwargs)
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outputs = generation_output.tolist()[0][len(inputs["input_ids"][0]):]
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generation_output = model.generate(input_ids=input_ids, **gen_kwargs)
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outputs = generation_output.tolist()[0][len(input_ids[0]):]
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response = tokenizer.decode(outputs, skip_special_tokens=True)
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history = history + [(query, response)]
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return response, history
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@ -83,8 +83,8 @@ def format_example(query):
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def predict(input, chatbot, max_length, top_p, temperature, history):
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chatbot.append((parse_text(input), ""))
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inputs = tokenizer([format_example(input)], return_tensors="pt")
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inputs = inputs.to(model.device)
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input_ids = tokenizer([format_example(input)], return_tensors="pt")["input_ids"]
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input_ids = input_ids.to(model.device)
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gen_kwargs = {
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"do_sample": True,
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"top_p": top_p,
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@ -94,8 +94,8 @@ def predict(input, chatbot, max_length, top_p, temperature, history):
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"repetition_penalty": 1.0
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}
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with torch.no_grad():
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generation_output = model.generate(**inputs, **gen_kwargs)
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outputs = generation_output.tolist()[0][len(inputs["input_ids"][0]):]
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generation_output = model.generate(input_ids=input_ids, **gen_kwargs)
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outputs = generation_output.tolist()[0][len(input_ids[0]):]
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response = tokenizer.decode(outputs, skip_special_tokens=True)
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history = history + [(input, response)]
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chatbot[-1] = (parse_text(input), parse_text(response))
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