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import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_name = "georgesung/llama2_7b_chat_uncensored"
tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False)
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype=torch.float16,
device_map="auto"
)
def chat(prompt):
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(
**inputs,
max_new_tokens=256,
do_sample=True,
temperature=0.7,
top_p=0.9
)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
demo = gr.Interface(
fn=chat,
inputs=gr.Textbox(lines=3, placeholder="Type your message here..."),
outputs="text",
title="Llama2 7B Uncensored Chatbot"
)
demo.launch() |