Instructions to use hf-tiny-model-private/tiny-random-RemBertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-RemBertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-tiny-model-private/tiny-random-RemBertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RemBertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-RemBertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 164835f574a1fd6827176162b45e406980203a84169b9721771f98db53167376
- Size of remote file:
- 62.4 MB
- SHA256:
- e720eb81de756083f1f8a7833a18b9e30e73d8aa3d73ab296eefe9f4bb0fa817
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