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distilbert-base-uncased-finetuned-quantized

Text Classification
Transformers.js
ONNX
distilbert
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Omar S osanseviero commited on
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Duplicate from osanseviero/distilbert-base-uncased-finetuned-quantized

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Co-authored-by: Omar Sanseviero <osanseviero@users.noreply.huggingface.co>

Files changed (9) hide show
  1. .gitattributes +34 -0
  2. README.md +37 -0
  3. config.json +33 -0
  4. onnx/model.onnx +3 -0
  5. onnx/model_quantized.onnx +3 -0
  6. special_tokens_map.json +7 -0
  7. tokenizer.json +0 -0
  8. tokenizer_config.json +15 -0
  9. vocab.txt +0 -0
.gitattributes ADDED
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+ *.npz filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ library_name: "transformers.js"
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+ ---
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+
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+ https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english with ONNX weights to be compatible with Transformers.js.
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+
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+ Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).
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+
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+ <html>
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+ <head>
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+ <script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
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+ <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
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+ </head>
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+ </html>
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+
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+ <gradio-lite>
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+
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+ <gradio-requirements>
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+ transformers_js_py
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+ </gradio-requirements>
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+
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+ <gradio-file name="app.py" entrypoint>
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+ from transformers_js import import_transformers_js
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+ import gradio as gr
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+
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+ transformers = await import_transformers_js()
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+ pipeline = transformers.pipeline
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+ pipe = await pipeline('sentiment-analysis', 'osanseviero/distilbert-base-uncased-finetuned-quantized')
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+
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+ async def classify(text):
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+ return await pipe(text)
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+
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+ demo = gr.Interface(classify, "textbox", "json")
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+ demo.launch()
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+ </gradio-file>
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+
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+ </gradio-lite>
config.json ADDED
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+ {
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+ "_name_or_path": "distilbert-base-uncased-finetuned-sst-2-english",
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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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+ "finetuning_task": "sst-2",
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+ "hidden_dim": 3072,
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+ "id2label": {
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+ "0": "NEGATIVE",
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+ "1": "POSITIVE"
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+ "POSITIVE": 1
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+ },
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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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+ "output_past": true,
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+ "pad_token_id": 0,
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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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+ "transformers_version": "4.29.2",
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+ "vocab_size": 30522
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+ }
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special_tokens_map.json ADDED
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+ {
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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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+ }
tokenizer.json ADDED
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tokenizer_config.json ADDED
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+ {
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+ "clean_up_tokenization_spaces": true,
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+ "cls_token": "[CLS]",
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+ "do_basic_tokenize": true,
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+ "tokenize_chinese_chars": true,
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+ "tokenizer_class": "DistilBertTokenizer",
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+ }
vocab.txt ADDED
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