Text Classification
Transformers
ONNX
English
deberta-v2
ai-safety
prompt-injection-defender
jailbreak-defender
adversarial-input-detection
text-embeddings-inference
Instructions to use Yeger/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yeger/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Yeger/test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Yeger/test") model = AutoModelForSequenceClassification.from_pretrained("Yeger/test") - Notebooks
- Google Colab
- Kaggle
Change confog
Browse files- config.json +10 -1
config.json
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"torch_dtype": "float32",
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"transformers_version": "4.55.4",
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"type_vocab_size": 0,
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"vocab_size": 128100
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}
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"torch_dtype": "float32",
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"transformers_version": "4.55.4",
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"type_vocab_size": 0,
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"vocab_size": 128100,
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"transformers.js_config": {
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"kv_cache_dtype": {
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"q4f16": "float16",
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"fp16": "float16"
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},
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"use_external_data_format": {
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"model.onnx": true
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}
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}
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}
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