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Upload app.py
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app.py
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@@ -8,6 +8,8 @@ import torch
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from huggingface_hub import hf_hub_download
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import transformers
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from transformers import BertModel, BertTokenizer
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class_names = ['Not Depressed', 'Depressed']
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pt_file = hf_hub_download(repo_id="liangc40/sentimental_analysis", filename="model.pt")
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@@ -36,11 +38,12 @@ def analyse(text):
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pad_to_max_length=True,
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return_attention_mask=True,
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return_tensors='pt')
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outputs = model(input_ids = encoding['input_ids'], attention_mask = encoding['attention_mask'])
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_, preds = torch.max(outputs, dim=1)
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#print(preds)
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return
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with gr.Blocks() as demo:
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gr.Markdown("<h1><center>Sentiment Analysis with Fine-tuned BERT Model")
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from huggingface_hub import hf_hub_download
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import transformers
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from transformers import BertModel, BertTokenizer
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from PIL import Image
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import requests
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class_names = ['Not Depressed', 'Depressed']
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pt_file = hf_hub_download(repo_id="liangc40/sentimental_analysis", filename="model.pt")
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pad_to_max_length=True,
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return_attention_mask=True,
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return_tensors='pt')
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face_url = "https://raw.githubusercontent.com/liangc40/ID2223_Sentimental_Analysis_Project/main/Image/"+ str(preds) + ".png"
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outputs = model(input_ids = encoding['input_ids'], attention_mask = encoding['attention_mask'])
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_, preds = torch.max(outputs, dim=1)
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img = Image.open(requests.get(face_url, stream=True).raw)
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#print(preds)
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return img
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with gr.Blocks() as demo:
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gr.Markdown("<h1><center>Sentiment Analysis with Fine-tuned BERT Model")
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