Instructions to use StatsGary/token_classification_wnut with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StatsGary/token_classification_wnut with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="StatsGary/token_classification_wnut")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("StatsGary/token_classification_wnut") model = AutoModelForTokenClassification.from_pretrained("StatsGary/token_classification_wnut", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5bdcbd1b56ef0f976756dd8790bfd7979503f040ecaa65f85dcff4c5ffaa9f2a
- Size of remote file:
- 1.34 GB
- SHA256:
- 016c50bfa91ac8396662b2ca37f02c42f135cf1252cac2d1468d960929ec5a6e
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