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import os | |
os.system('pip install minijinja') | |
import gradio as gr | |
from huggingface_hub import InferenceClient | |
import torch | |
import spaces | |
# Initialize the client with your model | |
client = InferenceClient("karpathy/gpt2_1558M_final2_hf") | |
def generate_text(prompt, max_tokens, temperature, top_p): | |
response = "" | |
for chunk in client.text_generation( | |
prompt, | |
max_new_tokens=max_tokens, | |
stream=True, | |
temperature=temperature, | |
top_p=top_p, | |
): | |
if isinstance(chunk, str): | |
response += chunk | |
elif hasattr(chunk, 'token'): | |
response += chunk.token.text | |
elif hasattr(chunk, 'generated_text'): | |
response += chunk.generated_text | |
yield response | |
if not response: | |
yield "I apologize, but I couldn't generate a response." | |
def clear_input(): | |
return "" | |
# Define example prompts | |
unicorn_example = "In a shocking finding, scientist discovered a herd of unicorns living in a remote, previously unexplored valley, in the Andes Mountains. Even more surprising to the researchers was the fact that the unicorns spoke perfect English." | |
time_travel_example = "Explain the grandfather paradox in time travel and propose a potential resolution." | |
with gr.Blocks() as demo: | |
gr.Markdown("<h1 style='text-align: center;'>LLM.C 1.5B Demo π€</h1>") | |
gr.Markdown( | |
""" | |
## About LLM.C | |
Quick demo of the model trained https://github.com/karpathy/llm.c/discussions/677 (add more info) | |
""" | |
) | |
with gr.Accordion("Advanced Settings", open=False): | |
max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max New Tokens") | |
temperature = gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.1, label="Temperature") | |
top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (Nucleus Sampling)") | |
gr.Markdown("### Example prompts") | |
with gr.Row(): | |
example1 = gr.Button("π¦ Unicorn Discovery") | |
example2 = gr.Button("β³ Time Travel Paradox") | |
prompt = gr.Textbox(lines=3, label='Enter your prompt') | |
output = gr.Textbox(lines=10, label='Generated text') | |
with gr.Row(): | |
clear_button = gr.Button("π§Ή Clear input") | |
submit = gr.Button("π Generate") | |
stop_button = gr.Button("π Stop") | |
# Set up event handlers | |
submit_event = submit.click(generate_text, inputs=[prompt, max_tokens, temperature, top_p], outputs=output) | |
stop_button.click(fn=None, inputs=None, outputs=None, cancels=[submit_event]) | |
clear_button.click(clear_input, inputs=[], outputs=prompt) | |
example1.click(lambda: unicorn_example, inputs=[], outputs=prompt) | |
example2.click(lambda: time_travel_example, inputs=[], outputs=prompt) | |
if __name__ == "__main__": | |
demo.launch() |