Added quantum circuit probability predictor model

app (3).py

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+from flask import Flask, render_template, request, jsonify
+from chat import chatbot
+
+app = Flask(__name__)
+
+
+@app.route("/")
+def hello():
+    return render_template('chat.html')
+
+@app.route("/ask", methods=['POST'])
+def ask():
+
+    message = str(request.form['messageText'])
+
+    bot_response = chatbot(message) 
+
+    return jsonify({'status':'OK','answer':bot_response})
+
+
+if __name__ == "__main__":
+    app.run()

chat (1).py

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+from peft import AutoPeftModelForCausalLM
+from transformers import GenerationConfig
+from transformers import AutoTokenizer
+import torch
+tokenizer = AutoTokenizer.from_pretrained("Vasanth/mistral-finetuned-alpaca")
+
+model = AutoPeftModelForCausalLM.from_pretrained(
+    "Vasanth/mistral-finetuned-alpaca",
+    low_cpu_mem_usage=True,
+    return_dict=True,
+    torch_dtype=torch.float16,
+    device_map="cuda")
+
+generation_config = GenerationConfig(
+    do_sample=True,
+    top_k=1,
+    temperature=0.1,
+    max_new_tokens=100,
+    pad_token_id=tokenizer.eos_token_id
+)
+
+def chatbot(message):
+    input_str = "###Human: " + message + " ###Assistant: "
+    inputs = tokenizer(input_str, return_tensors="pt").to("cuda")
+    outputs = model.generate(**inputs, generation_config=generation_config)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True).replace(input_str, '')

config (1).py

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+##OPEN API STUFF
+OPENAI_API_KEY = "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"