Token Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use oyvindgrutle/distilbert-base-uncased-test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oyvindgrutle/distilbert-base-uncased-test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="oyvindgrutle/distilbert-base-uncased-test2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("oyvindgrutle/distilbert-base-uncased-test2") model = AutoModelForTokenClassification.from_pretrained("oyvindgrutle/distilbert-base-uncased-test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a7410a9e2a5eb4a18a40cbcef3c12548e78d8966986fb8d3f969dd457a31990
- Size of remote file:
- 3.31 kB
- SHA256:
- 2ac5f5058eee3fc151840642d11ab8eb63610b7cc8d9b276c2ad63819625cbc1
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