Instructions to use mbruton/gal_ptsp_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_ptsp_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_ptsp_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_ptsp_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_ptsp_XLM-R") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ed245f538459706fd0ea0e3c3964204e5b5d70cf03d5a89b818ce42894dfb26
- Size of remote file:
- 623 Bytes
- SHA256:
- b14881f8352737c801b7e15ff2544419ace05937680ded1c03cfe4be45005e78
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