NanoGPT / app.py
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import torch
import gradio as gr
import random
from config import device_type, ckpt_path, GPTConfig, GPT, encode, decode, ctx, num_samples, max_new_tokens, temperature, top_k
checkpoint = torch.load(ckpt_path, map_location=device_type)
gptconf = GPTConfig(**checkpoint['model_args'])
model = GPT(gptconf)
state_dict = checkpoint['model']
unwanted_prefix = '_orig_mod.'
for k,v in list(state_dict.items()):
if k.startswith(unwanted_prefix):
state_dict[k[len(unwanted_prefix):]] = state_dict.pop(k)
model.load_state_dict(state_dict)
model.eval()
model.to(device_type)
def fn_query_on_load():
return "in the air and"
def generate_commentary(start):
start_ids = encode(start)
x = (torch.tensor(start_ids, dtype=torch.long, device=device_type)[None, ...])
out_text = ''
with torch.no_grad():
with ctx:
for k in range(num_samples):
y = model.generate(x, max_new_tokens, temperature=temperature, top_k=top_k)
out_text += decode(y[0].tolist())
out_text += '\n-o-o-o-o-o-o-o-\n\n'
return {
output: out_text
}
with gr.Blocks() as app:
with gr.Row():
gr.Markdown(
"""
# NanoGPT - Cricket Commentary Generative AI
### Give a prompt and see how it comes out with cricket commentary :)
""")
with gr.Row(visible=True):
search_text = gr.Textbox(value=fn_query_on_load, placeholder='Enter prompt..', label='Enter Prompt')
with gr.Row():
submit_btn = gr.Button("Submit", variant='primary')
clear_btn = gr.ClearButton()
with gr.Row():
with gr.Row():
output = gr.Textbox(lines=15, interactive=False, label='Commentary Box')
def clear_data():
return {
output: None,
search_text: None
}
clear_btn.click(clear_data, None, [output, search_text])
submit_btn.click(
generate_commentary,
search_text,
output
)
'''
Launch the app
'''
app.queue().launch()