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| import streamlit as st | |
| from huggingface_hub import hf_hub_download | |
| from llama_cpp import Llama | |
| # Hugging Face model repo details | |
| HF_MODEL_REPO = "anush76/unsloth-model" | |
| MODEL_FILENAME = "unsloth.Q4_K_M.gguf" | |
| # Download model from Hugging Face Hub | |
| st.sidebar.write("📥 Downloading model from Hugging Face...") | |
| model_path = hf_hub_download(repo_id=HF_MODEL_REPO, filename=MODEL_FILENAME) | |
| # Load the model with llama-cpp-python | |
| st.sidebar.write("🔄 Loading model...") | |
| llm = Llama(model_path=model_path, n_threads=8, n_batch=512, n_gpu_layers=20) | |
| # Streamlit UI | |
| st.title("🦥 Unsloth Chatbot") | |
| st.write("💬 Ask me anything!") | |
| user_input = st.text_input("You:") | |
| if user_input: | |
| response = llm.create_completion( | |
| prompt=f"Answer in a clear paragraph format:\n\n{user_input}", | |
| max_tokens=300, # Ensures a complete response | |
| temperature=0.6, | |
| top_p=0.9, | |
| stream=False # Disables word-by-word output | |
| ) | |
| full_response = response["choices"][0]["text"].strip() | |
| # Format response into a paragraph | |
| st.write("🤖 Chatbot:\n\n", full_response) | |