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:
- 8c4b64b09b212e343d2a0e319426297b9a299730b2e97fdf499e81eee3dfae28
- Size of remote file:
- 1.11 GB
- SHA256:
- 45e431f875ecf463962ddfb6fc41a7c741678209aa96372379a257bb0be48b21
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