Instructions to use hf-internal-testing/tiny-random-RobertaForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RobertaForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-RobertaForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RobertaForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-RobertaForTokenClassification") - Notebooks
- Google Colab
- Kaggle
Upload ONNX weights (#2)
Browse files- Upload ONNX weights (8d1ab12af459cbff5413834257ed87d9e7efb359)
- onnx/model.onnx +3 -0
onnx/model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:84bcac899b9f49322252b5675b2e7cf4486fd7d2f5f46ceba9b76e12ab542974
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size 472191
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