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from fastapi import FastAPI | |
from transformers import AutoModelForCausalLM, AutoTokenizer | |
# Create an instance of the FastAPI class | |
app = FastAPI() | |
# Define a route for the root endpoint | |
async def read_root(): | |
device = "cpu" | |
model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") | |
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") | |
text = """<s>[INST] What is your favourite condiment? [/INST] | |
""" | |
encodeds = tokenizer(text, return_tensors="pt", add_special_tokens=False) | |
model_inputs = encodeds.to(device) | |
model.to(device) | |
generated_ids = model.generate(**model_inputs, max_new_tokens=1000, do_sample=True) | |
decoded = tokenizer.batch_decode(generated_ids) | |
print(decoded[0]) | |
return {"message": decoded[0]} | |