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:
- 0a5f644f7eba1cc6f9324e102d5dffd2028804287bcd8a3b86f422ddd981ff15
- Size of remote file:
- 4.7 MB
- SHA256:
- 67ce12ea4550e57af39217a75686a61695e34edbb1c9892f82f0b861d73a4482
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