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import streamlit as st
from transformers import AutoModelForCausalLM, AutoTokenizer
def main():
st.title("Chatbot with Hugging Face Model")
model_id = "mistralai/Mixtral-8x7B-Instruct-v0.1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
user_input = st.text_input("User Input:", "What is your favourite condiment?")
if st.button("Generate Response"):
messages = [
{"role": "user", "content": user_input},
{"role": "assistant", "content": "Placeholder assistant message"} # You can modify this as needed
]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")
outputs = model.generate(inputs, max_new_tokens=20)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
st.text_area("Assistant's Response:", response)
if __name__ == "__main__":
main()
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