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from flask import Flask, request, jsonify
from transformers import AutoModel, AutoTokenizer
import torch
app = Flask(__name__)
# Load PhoBERT
tokenizer = AutoTokenizer.from_pretrained("vinai/phobert-base")
model = AutoModel.from_pretrained("vinai/phobert-base")
@app.route('/embed', methods=['POST'])
def embed():
data = request.get_json()
text = data.get('text', '')
if not text:
return jsonify({"error": "No text provided"}), 400
inputs = tokenizer(text, return_tensors="pt")
with torch.no_grad():
outputs = model(**inputs)
# Lấy embedding từ hidden state đầu tiên
embedding = outputs.last_hidden_state[:, 0, :].squeeze().tolist()
return jsonify({"embedding": embedding})
@app.route('/', methods=['GET'])
def index():
return "PhoBERT Space is running!"
if __name__ == "__main__":
app.run(host="0.0.0.0", port=7860)
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