Instructions to use Davlan/afro-xlmr-base-76L_script with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/afro-xlmr-base-76L_script with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Davlan/afro-xlmr-base-76L_script")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Davlan/afro-xlmr-base-76L_script") model = AutoModelForMaskedLM.from_pretrained("Davlan/afro-xlmr-base-76L_script", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Davlan/afro-xlmr-base-76L_script: direct link, hf CLI and curl.
- Browser
- Download file 6.07 kB
-
https://huggingface.co/Davlan/afro-xlmr-base-76L_script/resolve/main/training_args.bin
- Command line
-
hf download hf://Davlan/afro-xlmr-base-76L_script/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Davlan/afro-xlmr-base-76L_script/resolve/main/training_args.bin
6.07 kB
- Xet hash:
- d609c115d12df4544359514be8a86b7bba434df0974eb02f711fb21ff46d3158
- Size of remote file:
- 6.07 kB
- SHA256:
- 1b297164457bc4c126ab2fa2dd622c44113448fff3b9049f5b117f187319c3e9
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