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from transformers import AutoTokenizer, AutoModelForCausalLM | |
model_name = "google/gemma-2b" | |
tokenizer = AutoTokenizer.from_pretrained(model_name) | |
model = AutoModelForCausalLM.from_pretrained(model_name) | |
def generate_answers(query): | |
input_ids = tokenizer(query, return_tensors="pt") | |
output = model.generate(**input_ids) | |
return tokenizer.decode(output[0]) |