Text Classification
Transformers
Safetensors
Portuguese
deberta-v2
prompt-injection
security
guardrail
deberta
brazilian-portuguese
text-embeddings-inference
Instructions to use intelliway/deberta-v3-guardrail-mapa-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelliway/deberta-v3-guardrail-mapa-V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelliway/deberta-v3-guardrail-mapa-V2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelliway/deberta-v3-guardrail-mapa-V2") model = AutoModelForSequenceClassification.from_pretrained("intelliway/deberta-v3-guardrail-mapa-V2") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- model.safetensors +1 -1
- tokenizer_config.json +1 -1
model.safetensors
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version https://git-lfs.github.com/spec/v1
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tokenizer_config.json
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"sp_model_kwargs": {},
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"split_by_punct": false,
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"stride": 0,
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"tokenizer_class": "
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"truncation_side": "right",
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"truncation_strategy": "longest_first",
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"unk_token": "[UNK]",
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"sp_model_kwargs": {},
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"split_by_punct": false,
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"stride": 0,
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"tokenizer_class": "DebertaV2TokenizerFast",
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"truncation_side": "right",
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"truncation_strategy": "longest_first",
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"unk_token": "[UNK]",
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