Instructions to use mbruton/gal_en_mBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_en_mBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_en_mBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_en_mBERT") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_en_mBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8109eae64947f09928b67c72ac1db11fcaafd85af93ffaecd6ee8a35b6754ebf
- Size of remote file:
- 1.42 GB
- SHA256:
- c5d8973f363cfc6d8de8d44368d7778f6dbe6e2b079346fcea0c455397c2576e
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