Instructions to use hf-tiny-model-private/tiny-random-IBertForTokenClassification 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-IBertForTokenClassification 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-IBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-IBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-IBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 234b141c7ce4b83b0ff7b3619abed047a58d39da9935ad49257cff9381122ea3
- Size of remote file:
- 725 kB
- SHA256:
- 4bb8ce3bf1d1aa14dcff346d3e9004bf462095d3782437773ba536a7c62f3df0
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