Instructions to use Venkatesh4342/Event_Check with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Venkatesh4342/Event_Check with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Venkatesh4342/Event_Check")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Venkatesh4342/Event_Check") model = AutoModelForSequenceClassification.from_pretrained("Venkatesh4342/Event_Check") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- config.json +1 -1
- model_quantized.onnx +1 -1
config.json
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"_name_or_path": "/tmp/
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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"_name_or_path": "/tmp/tmpw7l8x8hj",
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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model_quantized.onnx
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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 sha256:94408693fd3fe34faab1ebce049b08409329dbd05efb154b2bcbccf433e9f73b
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size 67391937
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