import streamlit as st from transformers import AutoModelForCausalLM, AutoTokenizer import torch st.title("WhiteRabbitNeo Chatbot") # Load Model @st.cache_resource def load_model(): model_name = "path/to/chatbot_files" tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16) return tokenizer, model tokenizer, model = load_model() # Chat Interface user_input = st.text_input("You:", placeholder="Type your message here...") if user_input: inputs = tokenizer.encode(user_input, return_tensors="pt") outputs = model.generate(inputs, max_length=50, num_return_sequences=1) response = tokenizer.decode(outputs[0], skip_special_tokens=True) st.write(f"Chatbot: {response}") def load_model(): model_name = "C:/Users/DMJ/WhiteRabbitNeo-13B-v1/chatbot_files" # Use forward slashes for compatibility tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16) return tokenizer, model