app.py

import gradio as gr

import torch
# from transformers import pipeline
import huggingface_hub

import os

hf_token = os.getenv('HF_TOKEN')

huggingface_hub.login(token=hf_token)

model_id = "meta-llama/Llama-3.2-3B-Instruct"
messages = [
    {"role": "user", "content": "Who are you?"},
]

# device = "cuda" if torch.cuda.is_available() else "cpu"
# pipe = pipeline("text-generation", model="deepseek-ai/DeepSeek-R1", trust_remote_code=True, device=device)

from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-R1", trust_remote_code=True)

messages = [
    {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
    {"role": "user", "content": "Who are you?"},
]

def model(params):
    outputs = pipe(
    messages,
    max_new_tokens=256,
    )
    output = outputs[0]["generated_text"][-1]
    print(output)
    return output

app = gr.Interface(fn=model, inputs="textbox", outputs="textbox")
app.launch()