Instructions to use hf-internal-testing/tiny-random-RoCBertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RoCBertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-RoCBertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RoCBertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-RoCBertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ce02810b64e1de2f363cd88eab9dc33accf9038de747cb77cb21330c2a0006f
- Size of remote file:
- 3.05 MB
- SHA256:
- 4ac01d8c567c43c9f0a7088c1ac316dfa4d0b50a60480f29a48d6201c0dc56c4
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