Instructions to use mbruton/gal_pt_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_pt_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_pt_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_pt_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_pt_XLM-R", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e68afb1eca6628ba4171f29ef95dce868948294e2b33c02157cb69a16adb6b11
- Size of remote file:
- 3.5 kB
- SHA256:
- 515100ab657571787d5d22498b64c75583388363544b1e8e7367767afaab1970
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