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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
import gradio as gr
import torch
model_id = "tiiuae/falcon-rw-1b"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
pipe = pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
device=0 if torch.cuda.is_available() else -1,
)
def chat(user_input, history):
prompt = ""
for user, bot in history:
prompt += f"User: {user}\nBot: {bot}\n"
prompt += f"User: {user_input}\nBot:"
result = pipe(prompt, max_new_tokens=64, do_sample=False)
output = result[0]["generated_text"]
reply = output.split("Bot:")[-1].strip()
history.append((user_input, reply))
return history, history
gr.ChatInterface(
fn=chat,
chatbot=gr.Chatbot(),
title="Tiny Falcon Chatbot",
theme="default",
).launch()
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