Instructions to use hf-tiny-model-private/tiny-random-RemBertForTokenClassification 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-RemBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-RemBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RemBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-RemBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c872e96d021fd00380f1ed9a932d61f02b2b68adf7f1f2ee2344f5ba07c17180
- Size of remote file:
- 18.2 MB
- SHA256:
- 9f1bb42da93cf576605d83f19c78471b729228d807bba34e8f0db75aac7ebdd4
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