Instructions to use karthik19967829/XLM-R-es-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karthik19967829/XLM-R-es-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="karthik19967829/XLM-R-es-model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("karthik19967829/XLM-R-es-model") model = AutoModelForTokenClassification.from_pretrained("karthik19967829/XLM-R-es-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9305bad74abe8e4be65a58d35f0b345d09ea348f155923e6e85080989591e400
- Size of remote file:
- 2.93 kB
- SHA256:
- 5644a6321a05b839d0246753c46a97fe14916be4ffb78a3915efee946e1d8ced
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