Spaces:
Sleeping
Sleeping
Commit
Β·
a8fcc07
1
Parent(s):
d901f9e
Remove unused plotting function and clear button from sentiment analysis app
Browse files
app.py
CHANGED
|
@@ -4,8 +4,6 @@
|
|
| 4 |
from transformers import BertTokenizer, BertForSequenceClassification
|
| 5 |
import torch
|
| 6 |
import gradio as gr
|
| 7 |
-
import torch.nn.functional as F
|
| 8 |
-
import matplotlib.pyplot as plt
|
| 9 |
|
| 10 |
# Load saved model and tokenizer
|
| 11 |
model = BertForSequenceClassification.from_pretrained("./imdb_bert_model")
|
|
@@ -22,20 +20,6 @@ def predict_sentiment(text):
|
|
| 22 |
sentiment = "Positive π" if prediction == 1 else "Negative π "
|
| 23 |
return f"{sentiment} (Confidence: {confidence * 100:.2f}%)", probs.detach().numpy()[0]
|
| 24 |
|
| 25 |
-
# Plotting function for probabilities
|
| 26 |
-
def plot_probs(probs):
|
| 27 |
-
labels = ["Negative", "Positive"]
|
| 28 |
-
fig, ax = plt.subplots()
|
| 29 |
-
ax.bar(labels, probs, color=["red", "green"])
|
| 30 |
-
ax.set_ylim([0, 1])
|
| 31 |
-
ax.set_ylabel("Probability")
|
| 32 |
-
return fig
|
| 33 |
-
|
| 34 |
-
# Clear button handler
|
| 35 |
-
def clear_all():
|
| 36 |
-
return "", "", None
|
| 37 |
-
|
| 38 |
-
|
| 39 |
# Responsive UI with gr.Blocks
|
| 40 |
with gr.Blocks(theme=gr.themes.Soft()) as demo:
|
| 41 |
gr.Markdown("## π¬ IMDB Movie Review Sentiment Analyzer")
|
|
@@ -51,10 +35,8 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
|
|
| 51 |
autofocus=True
|
| 52 |
)
|
| 53 |
submit_btn = gr.Button("π Analyze")
|
| 54 |
-
clear_btn = gr.Button("π§Ή Clear")
|
| 55 |
with gr.Column(scale=1):
|
| 56 |
result_output = gr.Label(label="Predicted Sentiment")
|
| 57 |
-
prob_plot = gr.Plot(label="Confidence Scores")
|
| 58 |
|
| 59 |
gr.Examples(
|
| 60 |
examples=[
|
|
@@ -66,10 +48,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
|
|
| 66 |
inputs=[review_input]
|
| 67 |
)
|
| 68 |
|
| 69 |
-
submit_btn.click(fn=predict_sentiment, inputs=review_input, outputs=
|
| 70 |
-
clear_btn.click(fn=clear_all, outputs=[review_input, result_output, prob_plot])
|
| 71 |
-
|
| 72 |
gr.Markdown("### Made with β€οΈ by [Meet Mendapara](https://github.com/Meetmendapara09)")
|
| 73 |
|
| 74 |
-
# Launch the app
|
| 75 |
demo.launch(share=True)
|
|
|
|
| 4 |
from transformers import BertTokenizer, BertForSequenceClassification
|
| 5 |
import torch
|
| 6 |
import gradio as gr
|
|
|
|
|
|
|
| 7 |
|
| 8 |
# Load saved model and tokenizer
|
| 9 |
model = BertForSequenceClassification.from_pretrained("./imdb_bert_model")
|
|
|
|
| 20 |
sentiment = "Positive π" if prediction == 1 else "Negative π "
|
| 21 |
return f"{sentiment} (Confidence: {confidence * 100:.2f}%)", probs.detach().numpy()[0]
|
| 22 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 23 |
# Responsive UI with gr.Blocks
|
| 24 |
with gr.Blocks(theme=gr.themes.Soft()) as demo:
|
| 25 |
gr.Markdown("## π¬ IMDB Movie Review Sentiment Analyzer")
|
|
|
|
| 35 |
autofocus=True
|
| 36 |
)
|
| 37 |
submit_btn = gr.Button("π Analyze")
|
|
|
|
| 38 |
with gr.Column(scale=1):
|
| 39 |
result_output = gr.Label(label="Predicted Sentiment")
|
|
|
|
| 40 |
|
| 41 |
gr.Examples(
|
| 42 |
examples=[
|
|
|
|
| 48 |
inputs=[review_input]
|
| 49 |
)
|
| 50 |
|
| 51 |
+
submit_btn.click(fn=predict_sentiment, inputs=review_input, outputs=result_output)
|
|
|
|
|
|
|
| 52 |
gr.Markdown("### Made with β€οΈ by [Meet Mendapara](https://github.com/Meetmendapara09)")
|
| 53 |
|
|
|
|
| 54 |
demo.launch(share=True)
|