Instructions to use hf-internal-testing/tiny-random-MobileBertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MobileBertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MobileBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MobileBertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MobileBertModel") - Notebooks
- Google Colab
- Kaggle
Upload ONNX weights (#2)
Browse files- [Awaiting approval] Upload ONNX weights (01ea8f5abc55470390d08abd94a55b996dc747c9)
- 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 sha256:62faa62808d51d96b26b30ec49d2979d9f59d209b000d6d3610519c8e675a0a1
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size 2875180
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