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:
- 97be4de410a503b6db9537f9ea053ae736acba673f9419e57630907b66a14958
- Size of remote file:
- 266 MB
- SHA256:
- 4da8e0c514696e9901b0516f98cbc49aaaaddf622245e7c80dc6f9cc7dee5176
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