Create app.py

app.py

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+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("AdaptLLM/finance-LLM-13B")
+tokenizer = AutoTokenizer.from_pretrained("AdaptLLM/finance-LLM-13B", use_fast=False)
+
+
+# Put your input here:
+user_input = '''Use this fact to answer the question: Title of each class Trading Symbol(s) Name of each exchange on which registered
+Common Stock, Par Value $.01 Per Share MMM New York Stock Exchange
+MMM Chicago Stock Exchange, Inc.
+1.500% Notes due 2026 MMM26 New York Stock Exchange
+1.750% Notes due 2030 MMM30 New York Stock Exchange
+1.500% Notes due 2031 MMM31 New York Stock Exchange
+
+Which debt securities are registered to trade on a national securities exchange under 3M's name as of Q2 of 2023?'''
+
+# Simply use your input as the prompt for base models
+prompt = user_input
+
+inputs = tokenizer(prompt, return_tensors="pt", add_special_tokens=False).input_ids.to(model.device)
+outputs = model.generate(input_ids=inputs, max_length=2048)[0]
+
+answer_start = int(inputs.shape[-1])
+pred = tokenizer.decode(outputs[answer_start:], skip_special_tokens=True)
+
+print(f'### User Input:\n{user_input}\n\n### Assistant Output:\n{pred}')