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sentiement_analysis.py

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+# -*- coding: utf-8 -*-
+"""sentiement_analysis.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1uCHkA4O7IFjR173CabfByPvjfbiz6wY7
+"""
+
+!pip install diffusers transformers torch numpy scipy gradio datasets
+
+!pip3 install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio===0.9.1 -f https://download.pytorch.org/whl/torch_stable.html
+
+import torch
+from transformers import AutoModelForSequenceClassification, AutoTokenizer, AutoConfig
+import numpy as np
+from scipy.special import softmax
+import gradio as gr
+torch.cuda.is_available()
+
+model_path = "cardiffnlp/twitter-roberta-base-sentiment-latest"
+
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+config = AutoConfig.from_pretrained(model_path)
+model = AutoModelForSequenceClassification.from_pretrained(model_path)
+
+def sentiment_analysis(text):
+    encoded_input = tokenizer(text, return_tensors='pt')
+    output = model(**encoded_input)
+    scores_ = output[0][0].detach().numpy()
+    scores_ = softmax(scores_)
+    labels = ['Negative', 'Neutral', 'Positive']
+    scores = {l: float(s) for (l, s) in zip(labels, scores_)}
+    return scores
+
+demo = gr.Interface(
+    theme=gr.themes.Base(),
+    fn=sentiment_analysis,
+    inputs=gr.Textbox(placeholder="Write your text here..."),
+    outputs="label",
+    examples=[
+        ["I'm thrilled about the job offer!"],
+        ["The weather today is absolutely beautiful."],
+        ["I had a fantastic time at the concert last night."],
+        ["I'm so frustrated with this software glitch."],
+        ["The customer service was terrible at the store."],
+        ["I'm really disappointed with the quality of this product."]
+    ],
+    title='Sentiment Analysis App',
+    description='This app classifies a positive, neutral, or negative sentiment.'
+)
+
+demo.launch()
+
+!ls
+!git add app.py
+!git commit -m "app.py"
+#!git push
+#!git push
+
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+from huggingface_hub import notebook_login
+
+notebook_login()
+
+model.push_to_hub("Kiro0o/bert-sentiment-analysis")
+tokenizer.push_to_hub("Kiro0o/bert-sentiment-analysis")
+
+!git clone https://huggingface.co/spaces/Kiro0o/Sentiment