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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ec1e16392162ea406fd5dc7afb4f7889db97be8e9b14cde850cf3b0d8635ace
- Size of remote file:
- 62.4 MB
- SHA256:
- d95cfadc291f8674bbb8828568b9b72d6340ec4c5d898a22f32e208ba13fc946
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