Instructions to use Jethuestad/distilbert-base-uncased-test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jethuestad/distilbert-base-uncased-test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Jethuestad/distilbert-base-uncased-test2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Jethuestad/distilbert-base-uncased-test2") model = AutoModelForTokenClassification.from_pretrained("Jethuestad/distilbert-base-uncased-test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35e485f572fce30f8881a2fd350da0bfd5471f8b4dd2db28d7eab4f8d1b08516
- Size of remote file:
- 266 MB
- SHA256:
- 21da1bbd7fc39ab26816e6167e3c55477a20b016652eb0bab8ac74c7e398b56e
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