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Create app.py
Verified signatureimport streamlit as st from transformers import AutoModelForCausalLM, AutoTokenizer import torch # Load the model and tokenizer @st.cache_resource def load_model(): model_name = "prithivMLmods/QwQ-LCoT-14B-Conversational" tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForCausalLM.from_pretrained( model_name, device_map="auto", # Automatically assign to CPU/GPU torch_dtype=torch.float16, # Mixed precision for large models ) return tokenizer, model # Load resources tokenizer, model = load_model() # Streamlit app UI st.title("QwQ-LCoT Chatbot") st.write("A conversational AI powered by QwQ-LCoT-14B. Ask me anything!") # User input user_input = st.text_input("You: ", "") if st.button("Send"): if user_input.strip(): with st.spinner("Generating response..."): # Tokenize input inputs = tokenizer(user_input, return_tensors="pt") # Generate response outputs = mod…d4439d6 -
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