hugging face uploaded main elements

app.py

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+import gradio as gr
+from transformers import BertTokenizer, BertForSequenceClassification
+import torch
+
+# Load the tokenizer and model
+model_path = "laptop_data.pkl"  # Replace with the actual path
+tokenizer = BertTokenizer.from_pretrained(model_path)
+model = BertForSequenceClassification.from_pretrained(model_path)
+
+# Set the model to evaluation mode
+model.eval()
+
+
+def classify_text(text):
+    inputs = tokenizer(text, return_tensors="pt",
+                       padding=True, truncation=True)
+    with torch.no_grad():
+        outputs = model(**inputs)
+    logits = outputs.logits
+    probabilities = torch.softmax(logits, dim=1)
+    return probabilities[0].tolist()
+
+
+iface = gr.Interface(
+    fn=classify_text,
+    inputs=gr.inputs.Textbox(),
+    outputs=gr.outputs.Label(num_top_classes=2),
+    live=True,
+    interpretation="default"
+)
+
+iface.launch()

laptop_data.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e2ef9db05bf1455d35939d2bc1cecef60ec94ddf364c114612a441cf303d2dd4
+size 328602971

requirements.txt

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+gradio==3.17.0
+onnxruntime==1.15.0
+torch==1.13.1
+transformers==4.26.0