Upload sentment.py

sentment.py

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+# -*- coding: utf-8 -*-
+"""Sentment.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1ivaq7Q88JAMMQT4pr7ms9q6ZxAR4niVn
+"""
+
+!pip install transformers
+
+!pip install gradio
+
+import gradio as gr
+from transformers import pipeline
+
+# Load the pre-trained model
+classifier = pipeline('sentiment-analysis')
+
+# Define the prediction function
+def predict_sentiment(text):
+    results = classifier(text)
+    return results[0]['label'], results[0]['score']
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=predict_sentiment,
+    inputs="text",
+    outputs=["text", "number"],
+    title="Sentiment Analysis",
+    description="Enter text to classify its sentiment as positive or negative."
+)
+
+# Launch the interface
+iface.launch()
+
+import torch
+from transformers import DistilBertTokenizer, DistilBertForSequenceClassification
+
+tokenizer = DistilBertTokenizer.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english")
+model = DistilBertForSequenceClassification.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english")
+
+inputs = tokenizer("my friend is no more i am sad", return_tensors="pt")
+with torch.no_grad():
+    logits = model(**inputs).logits
+
+predicted_class_id = logits.argmax().item()
+model.config.id2label[predicted_class_id]
+
+!git clone https://huggingface.co/spaces/Priyanhsu/Sentiment_analysis