Instructions to use HugoGiddins/is_call_deberta_v3_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HugoGiddins/is_call_deberta_v3_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HugoGiddins/is_call_deberta_v3_small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HugoGiddins/is_call_deberta_v3_small") model = AutoModelForSequenceClassification.from_pretrained("HugoGiddins/is_call_deberta_v3_small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
tokenizer_config: drop transformers-5-only extra_special_tokens list (breaks 4.x load)
Browse files- tokenizer_config.json +2 -9
tokenizer_config.json
CHANGED
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@@ -5,15 +5,8 @@
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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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"extra_special_tokens": [
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"[PAD]",
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"[CLS]",
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"[SEP]"
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],
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"is_local": false,
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"local_files_only": false,
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"mask_token": "[MASK]",
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"model_max_length":
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"split_by_punct": false,
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@@ -21,4 +14,4 @@
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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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"cls_token": "[CLS]",
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"do_lower_case": false,
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"eos_token": "[SEP]",
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"mask_token": "[MASK]",
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"model_max_length": 224,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"split_by_punct": false,
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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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