Instructions to use hf-internal-testing/tiny-random-DebertaV2ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DebertaV2ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-DebertaV2ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForTokenClassification") - Notebooks
- Google Colab
- Kaggle
Upload ONNX weights (#2)
Browse files- [Awaiting approval] Upload ONNX weights (2963a5b097122938e8baa6fc7718d14185915243)
- onnx/model.onnx +3 -0
onnx/model.onnx
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oid sha256:a65c6b0d009efd14dfb93dbf3f7d2ab3fe0ee7c0aebac0ff07526407e2da73f2
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size 16823062
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