Create app.py

app.py

@@ -0,0 +1,20 @@
+from flask import Flask, request, jsonify
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+app = Flask(__name__)
+
+# Load model and tokenizer
+model_name = "meta-llama/LLaMA-2-7b"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+@app.route('/predict', methods=['POST'])
+def predict():
+    data = request.json
+    inputs = tokenizer(data['text'], return_tensors='pt')
+    outputs = model.generate(**inputs)
+    response_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return jsonify({'response': response_text})
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=5000)