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 training_args.bin from karthik19967829/XLM-R-ar-model: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/karthik19967829/XLM-R-ar-model/resolve/main/training_args.bin
- Command line
-
hf download hf://karthik19967829/XLM-R-ar-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/karthik19967829/XLM-R-ar-model/resolve/main/training_args.bin
2.93 kB
- Xet hash:
- 4d645b879debd22822c6d545cf0244672eaa1b26089759249e539312b4181bf6
- Size of remote file:
- 2.93 kB
- SHA256:
- b6173f9b702e4029a66f4a12c65decfd60fed43ecdb6776f750f603d2e9249a1
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