app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load your model from Hugging Face Hub
model_name = "deepseek-ai/DeepSeek-R1-Distill-Llama-70B-free"
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Function to generate text from the model
def generate_text(prompt):
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(inputs["input_ids"], max_length=50)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Set up Gradio Interface
iface = gr.Interface(fn=generate_text, inputs="text", outputs="text")

# Launch the app
iface.launch()