| # -*- coding: utf-8 -*- | |
| """ | |
| Created on Sat Oct 5 16:41:22 2024 | |
| @author: Admin | |
| """ | |
| import gradio as gr | |
| from transformers import pipeline | |
| import os | |
| from huggingface_hub import login | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| import torch | |
| chatbot = pipeline(model="microsoft/Phi-3.5-mini-instruct") | |
| #token = os.getenv("HF_TOKEN") | |
| #login(token = os.getenv('HF_TOKEN')) | |
| #chatbot = pipeline(model="meta-llama/Llama-3.2-1B") | |
| #tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.2-1B-Instruct") | |
| #model = AutoModelForCausalLM.from_pretrained( | |
| # "meta-llama/Llama-3.2-1B-Instruct", | |
| # device_map="auto", | |
| # torch_dtype="auto", | |
| #) | |
| #chatbot = pipeline(model="facebook/blenderbot-400M-distill") | |
| message_list = [] | |
| response_list = [] | |
| def vanilla_chatbot(message, history): | |
| #inputs = tokenizer(message, return_tensors="pt").to("cpu") | |
| #with torch.no_grad(): | |
| # outputs = model.generate(inputs.input_ids, max_length=100) | |
| #return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| conversation = chatbot(message) | |
| return conversation[0]['generated_text'] | |
| demo_chatbot = gr.ChatInterface(vanilla_chatbot, title="Vanilla Chatbot", description="Enter text to start chatting.") | |
| demo_chatbot.launch(True) |