Instructions to use hf-internal-testing/tiny-random-ModernBertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ModernBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-ModernBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ModernBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-ModernBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
Upload ONNX weights
Browse files- 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 sha256:7cf9858bb50a38c242f4a9ec2cdb494a95b02bfc227d03adb541f0fad2840b3f
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size 6691608
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