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# import gradio as gr
# from transformers import AutoModelForSequenceClassification, AutoTokenizer, BitsAndBytesConfig
# import torch
# # Set device to CPU since GPU quantization is unavailable
# device = 'cpu'
# # Set up 8-bit quantization with BitsAndBytesConfig
# quantization_config = BitsAndBytesConfig(
# load_in_8bit=True, # Enable 8-bit quantization
# llm_int8_enable_fp32_cpu_offload=True # Use CPU for 8-bit quantization operations
# )
# # Load the model with quantization configuration
# model_name = "Rahmat82/DistilBERT-finetuned-on-emotion"
# model = AutoModelForSequenceClassification.from_pretrained(
# model_name,
# quantization_config=quantization_config,
# device_map={"": device} # Ensures everything runs on CPU
# )
# tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
# def predict(query: str) -> dict:
# inputs = tokenizer(query, return_tensors='pt')
# inputs = {k: v.to(device) for k, v in inputs.items()} # Ensure inputs are on CPU
# outputs = model(**inputs)
# outputs = torch.sigmoid(outputs.logits)
# outputs = outputs.detach().cpu().numpy()
# # Define label to ID mapping
# label2ids = {
# "sadness": 0,
# "joy": 1,
# "love": 2,
# "anger": 3,
# "fear": 4,
# "surprise": 5,
# }
# for i, k in enumerate(label2ids.keys()):
# label2ids[k] = outputs[0][i]
# label2ids = {k: float(v) for k, v in sorted(label2ids.items(), key=lambda item: item[1], reverse=True)}
# return label2ids
# # Gradio interface setup
# demo = gr.Interface(
# theme=gr.themes.Soft(),
# title="RHM Emotion Classifier 😊",
# description="Beyond Words: Capturing the Essence of Emotion in Text<h3>On CPU with 8-bit quantization</h3>",
# fn=predict,
# inputs=gr.components.Textbox(label='Write your text here', lines=3),
# outputs=gr.components.Label(label='Predictions', num_top_classes=6),
# allow_flagging='never',
# examples=[
# ["The gentle touch of your hand on mine is a silent promise that echoes through the corridors of my heart."],
# ["The rain mirrored the tears I couldn't stop, each drop a tiny echo of the ache in my heart. The world seemed muted, colors drained, and a heavy weight settled upon my soul."],
# ["Walking through the dusty attic, I stumbled upon a hidden door. With a mix of trepidation and excitement, I pushed it open, expecting cobwebs and forgotten junk. Instead, a flood of sunlight revealed a secret garden, blooming with vibrant flowers and buzzing with life. My jaw dropped in pure astonishment."],
# ]
# )
# demo.launch(share=True)
import gradio as gr
from transformers import pipeline, AutoTokenizer
from optimum.onnxruntime import ORTModelForSequenceClassification
import torch
device = 'cuda' if torch.cuda.is_available() else 'cpu'
model_name = "Rahmat82/DistilBERT-finetuned-on-emotion"
model = ORTModelForSequenceClassification.from_pretrained(model_name, export=True)
tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
model.to(device)
def predict(query: str) -> dict:
inputs = tokenizer(query, return_tensors='pt')
inputs.to(device)
outputs = model(**inputs)
outputs = torch.sigmoid(outputs.logits)
outputs = outputs.detach().cpu().numpy()
label2ids = {
"sadness": 0,
"joy": 1,
"love": 2,
"anger": 3,
"fear": 4,
"surprise": 5,
}
for i, k in enumerate(label2ids.keys()):
label2ids[k] = outputs[0][i]
label2ids = {k: float(v) for k, v in sorted(label2ids.items(), key=lambda item: item[1], reverse=True)}
return label2ids
demo = gr.Interface(
theme = gr.themes.Soft(),
title = "RHM Emotion Classifier 😊",
description = "Beyond Words: Capturing the Essence of Emotion in Text<h3>On GPU it is much faster 🚀</h3>",
fn = predict,
inputs = gr.components.Textbox(label='Write your text here', lines=3),
outputs = gr.components.Label(label='Predictions', num_top_classes=6),
allow_flagging = 'never',
examples = [
["The gentle touch of your hand on mine is a silent promise that echoes through the corridors of my heart."],
["The rain mirrored the tears I couldn't stop, each drop a tiny echo of the ache in my heart. The world seemed muted, colors drained, and a heavy weight settled upon my soul."],
["Walking through the dusty attic, I stumbled upon a hidden door. With a mix of trepidation and excitement, I pushed it open, expecting cobwebs and forgotten junk. Instead, a flood of sunlight revealed a secret garden, blooming with vibrant flowers and buzzing with life. My jaw dropped in pure astonishment."],
]
)
demo.launch(share=True) |