Instructions to use karthik19967829/XLM-R-en-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karthik19967829/XLM-R-en-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="karthik19967829/XLM-R-en-model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("karthik19967829/XLM-R-en-model") model = AutoModelForTokenClassification.from_pretrained("karthik19967829/XLM-R-en-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a3c17aa6b430d87e3a91ebc16b63e2e3245e44d533bc35cb99771726eff593f
- Size of remote file:
- 1.11 GB
- SHA256:
- 92803e1c816335f689f579d0ae343c0d8ce2ba56f77b25e2a784d76faa2d0dc4
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