Instructions to use hf-internal-testing/tiny-random-RoFormerForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RoFormerForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-RoFormerForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RoFormerForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-RoFormerForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17a05031aa574362d61b205cdeca09f14a6c9c0af506b660bca8f9554705f87c
- Size of remote file:
- 6.68 MB
- SHA256:
- 7581a36ce2c115593eacd8dcd6473be33dd608ff1be5edeb4ea7ce357c0b1d57
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