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:
- 47ddc0313eab7239f20731412017bf4ed4b48ce29791a84e31c94b1dfb939a5b
- Size of remote file:
- 2.22 GB
- SHA256:
- 2e7f1fe50781b10deb9dc91fc1d9a7714869f070fb363a7da9a9ac5cff577c30
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