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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb426c62c7898bb7f24afb26937db3222c533814f4f347a382ac7f55894cbf59
- Size of remote file:
- 3.5 kB
- SHA256:
- 0f9a2b839aedd03c560da3cf76e7e124183422b6e1b1b85877dc764d43107103
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