Instructions to use hf-internal-testing/tiny-random-MobileBertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MobileBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-MobileBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MobileBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-MobileBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
Upload ONNX weights (#2)
Browse files- [Awaiting approval] Upload ONNX weights (5654d753c53582c093798ea988e24414293afc6f)
- 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:f34c72a3eb22adb0808e1bd724cc9dcc2b187220c5ced7e7a4df2b899db429d3
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size 2908077
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