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Upload 7 files
Browse files- app.py +31 -0
- model_save/config.json +25 -0
- model_save/pytorch_model.bin +3 -0
- model_save/special_tokens_map.json +7 -0
- model_save/tokenizer.json +0 -0
- model_save/tokenizer_config.json +14 -0
- model_save/vocab.txt +0 -0
app.py
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import torch
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import transformers
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from transformers import DistilBertTokenizerFast
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from transformers import DistilBertForSequenceClassification
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import gradio as gr
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# Load the pre-trained tokenizer
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tokenizer = DistilBertTokenizerFast.from_pretrained('./model_save/',local_files_only=True)
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# Load the pre-trained DilBERT model
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model = DistilBertForSequenceClassification.from_pretrained('./model_save/',local_files_only=True)
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model.eval()
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# Define a predict function
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def predict(text):
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encoding=tokenizer(text,return_tensors='pt')
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input_ids, attention_mask = encoding['input_ids'],encoding['attention_mask']
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outputs = model(input_ids,attention_mask=attention_mask)
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logits = outputs['logits']
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pred_label = torch.argmax(logits,1)[0]
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return 'Positive' if pred_label > 0.5 else 'Negative'
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# Initialize the Gradio interface
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title = "Write a movie review"
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description = "Enter a review for a movie you've seen. This tool will try to guess whether your review is positive or negative."
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gr.Interface(fn=predict,
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inputs="text",
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outputs="label",
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title = title,
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description = description,
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).launch()
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model_save/config.json
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{
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"_name_or_path": "distilbert-base-uncased",
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"initializer_range": 0.02,
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"problem_type": "single_label_classification",
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.20.1",
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"vocab_size": 30522
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}
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model_save/pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:7a619cd8c20b321c9442a77f080497fbc1d94e9340eab738fa80fd7b280086ea
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size 267854321
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model_save/special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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model_save/tokenizer.json
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model_save/tokenizer_config.json
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{
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"name_or_path": "distilbert-base-uncased",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"special_tokens_map_file": null,
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "DistilBertTokenizer",
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"unk_token": "[UNK]"
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}
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model_save/vocab.txt
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