Instructions to use mbruton/gal_sp_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_sp_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_sp_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_sp_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_sp_XLM-R") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8461975416738165a4a3876fa7debc797957a6cd4bf524a2bb3076977d546ba8
- Size of remote file:
- 1.11 GB
- SHA256:
- 278bd8f81f2edc24470acdf65f3b847ebfdf4f74836f81f4669aeb34b9276233
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