Instructions to use hf-internal-testing/tiny-random-RemBertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RemBertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-RemBertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RemBertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-RemBertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae1524ca093802c33a21ff5570fd19da0b95b25ba7690c1e19e84bb47fe218c6
- Size of remote file:
- 62.3 MB
- SHA256:
- 0f2bd2877b9ee79d047d952e46b64cdd14e5c36e44686a925c1bd805f8754820
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