llmc_1558M / app.py
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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")
@spaces.GPU
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 πŸ€–</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("πŸ¦„ Unicorn Discovery")
example2 = gr.Button("⏳ 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("🧹 Clear input")
submit = gr.Button("πŸš€ Generate")
stop_button = gr.Button("πŸ›‘ 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()