Instructions to use LLMDH/editorial-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LLMDH/editorial-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="LLMDH/editorial-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("LLMDH/editorial-detection") model = AutoModelForTokenClassification.from_pretrained("LLMDH/editorial-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 673f8f156aaf7b0324fd0d4e4987563cd92aaa7400d1f86c7d1616b60466be12
- Size of remote file:
- 5.18 kB
- SHA256:
- fb7845b8cfdcdf6aaf7bd25a4f748d7982b5deac775a33e553d58fbf6f5730f8
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