Token Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use mircoboettcher/bert-wnut17-optimized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mircoboettcher/bert-wnut17-optimized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mircoboettcher/bert-wnut17-optimized")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mircoboettcher/bert-wnut17-optimized") model = AutoModelForTokenClassification.from_pretrained("mircoboettcher/bert-wnut17-optimized") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 956be754f7f2da903abc1e89392f2ff6a69ad654a09588aeeecabcacbb85a913
- Size of remote file:
- 431 MB
- SHA256:
- 5929bf1db941cb0da6a38e23852b7a36f4ef271d916fe2f310ce0116b0ce36d4
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