Text Classification
Transformers
Safetensors
finance
nlp
classification
named-entity-recognition
hinglish
multilingual
audio
asr
Instructions to use rohin30n/Armour with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rohin30n/Armour with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rohin30n/Armour")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rohin30n/Armour", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload finance_classifier\tokenizer_config.json with huggingface_hub
Browse files
finance_classifier//tokenizer_config.json
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{
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"backend": "tokenizers",
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"cls_token": "[CLS]",
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"do_lower_case": false,
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"is_local": 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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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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