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import torch
import gradio as gr
from transformers import (
AutoConfig,
AutoTokenizer,
AutoModelForSequenceClassification
)
model_dir = "my-bert-model"
config = AutoConfig.from_pretrained(
model_dir,
finetuning_task="text-classification"
)
tokenizer = AutoTokenizer.from_pretrained(model_dir)
model = AutoModelForSequenceClassification.from_pretrained(
model_dir,
config=config
)
def inference(input_text):
inputs = tokenizer.batch_encode_plus(
[input_text],
max_length=512,
pad_to_max_length=True,
truncation=True,
padding="max_length",
return_tensors="pt",
)
with torch.no_grad():
logits = model(**inputs).logits
predicted_class_id = logits.argmax().item()
output = model.config.id2label[predicted_class_id]
return output
with gr.Blocks(css="""
.message.svelte-w6rprc.svelte-w6rprc.svelte-w6rprc {font-size: 20px; margin-top: 20px}
#component-21 > div.wrap.svelte-w6rprc {height: 600px;}
""") as demo:
with gr.Row():
with gr.Column():
input_text = gr.Textbox(
placeholder="Insert your prompt here:",
scale=2,
container=False
)
answer = gr.Textbox(lines=0, label="Answer")
generate_bt = gr.Button("Generate", scale=1)
inputs = [input_text]
outputs = [answer]
generate_bt.click(
fn=inference,
inputs=inputs,
outputs=outputs,
show_progress=True
)
examples = [
["My last two weather pics from the storm on August 2nd. People packed up real fast after the temp dropped and winds picked up.", 1],
["Lying Clinton sinking! Donald Trump singing: Let's Make America Great Again!", 0],
]
demo.queue()
demo.launch()
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