Instructions to use mbruton/gal_enptsp_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_enptsp_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_enptsp_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_enptsp_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_enptsp_XLM-R", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c84771390192d9123f98e5c1a73429c9104bf414243c09a183b78ea5ed8810bd
- Size of remote file:
- 3.5 kB
- SHA256:
- 6778ed24cf6bf0568cf36296b83fb334d11d1bda9442813c03d73deebe77bf90
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