Instructions to use hf-internal-testing/tiny-random-BertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-BertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-BertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
Upload ONNX weights (#2)
Browse files- [Awaiting approval] Upload ONNX weights (d4db712678d8cfd8ac7b1e9af49406292894564c)
- 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 sha256:31b0f425936892d1d223eaafcb6111ab49ff6835054ca1880734739f04fcea57
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size 472279
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