Instructions to use selsar/cv_social_deviance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selsar/cv_social_deviance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="selsar/cv_social_deviance")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("selsar/cv_social_deviance") model = AutoModelForSequenceClassification.from_pretrained("selsar/cv_social_deviance", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer matching best CV model
Browse files- tokenizer.json +2 -2
- tokenizer_config.json +5 -43
tokenizer.json
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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oid sha256:a43a63895b18495744e1f257fa161958c578612ec67b8e0b20d24d93cbcc56b9
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size 16014625
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tokenizer_config.json
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{
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"content": "[PAD]",
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"special": true
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"1": {
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"normalized": false,
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"single_word": false,
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"special": true
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"2": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"single_word": false,
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"special": true
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"3": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "[CLS]",
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": false,
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"eos_token": "[SEP]",
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"
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sp_model_kwargs": {},
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"split_by_punct": false,
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"tokenizer_class": "DebertaV2Tokenizer",
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"unk_token": "[UNK]",
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"vocab_type": "spm"
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}
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{
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"add_prefix_space": true,
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"backend": "tokenizers",
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"bos_token": "[CLS]",
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": false,
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"eos_token": "[SEP]",
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"is_local": true,
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"local_files_only": false,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sp_model_kwargs": {},
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"split_by_punct": false,
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"tokenizer_class": "DebertaV2Tokenizer",
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"unk_id": 3,
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"unk_token": "[UNK]",
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"vocab_type": "spm"
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}
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