Instructions to use karthik19967829/XLM-R-ar-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karthik19967829/XLM-R-ar-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="karthik19967829/XLM-R-ar-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("karthik19967829/XLM-R-ar-model") model = AutoModelForTokenClassification.from_pretrained("karthik19967829/XLM-R-ar-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from karthik19967829/XLM-R-ar-model: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/karthik19967829/XLM-R-ar-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://karthik19967829/XLM-R-ar-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/karthik19967829/XLM-R-ar-model/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 3bfe1c43144674037abb5615ae2e6f3c597560dc78888f94db59d475b5a6ebca
- Size of remote file:
- 1.11 GB
- SHA256:
- 1a2e91538be28f2cf0d66f5d096c6795ae0cd7ce9ae18e4e46534e0324531bb8
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