Instructions to use ruanchaves/xlm-roberta-base-harem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruanchaves/xlm-roberta-base-harem with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ruanchaves/xlm-roberta-base-harem")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ruanchaves/xlm-roberta-base-harem") model = AutoModelForTokenClassification.from_pretrained("ruanchaves/xlm-roberta-base-harem", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ruanchaves/xlm-roberta-base-harem: direct link, hf CLI and curl.
- Browser
- Download file 3.7 kB
-
https://huggingface.co/ruanchaves/xlm-roberta-base-harem/resolve/main/training_args.bin
- Command line
-
hf download hf://ruanchaves/xlm-roberta-base-harem/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ruanchaves/xlm-roberta-base-harem/resolve/main/training_args.bin
3.7 kB
- Xet hash:
- 81c7a4f87414c859f8d208bd209f06fd9bdd75ee505956d080772f400713845b
- Size of remote file:
- 3.7 kB
- SHA256:
- ba126d24cb3f6013f4274354aac84d0f9b9ba192342fdbc5b734727ec1d097ae
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