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6a13310 9684b82 6a13310 9684b82 6a13310 9684b82 6a13310 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | from flask import Flask, request, jsonify
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
app = Flask(__name__)
# Load base model and tokenizer
MODEL_NAME = "meta-llama/Llama-2-7b-chat-hf" # Change this to your base model
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype=torch.float16, device_map="auto")
@app.route("/predict", methods=["POST"])
def predict():
data = request.json
input_text = data.get("text", "")
# Tokenize input
inputs = tokenizer(input_text, return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_length=200)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
return jsonify({"response": response})
if __name__ == "__main__":
app.run(host="0.0.0.0", port=7860)
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