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# -*- 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
#chatbot = pipeline(model="NCSOFT/Llama-3-OffsetBias-8B")
#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")
model = AutoModelForCausalLM.from_pretrained(
"meta-llama/Llama-3.2-1B",
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['text'], 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) |