Instructions to use Davlan/afro-xlmr-large-76L_script with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/afro-xlmr-large-76L_script with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Davlan/afro-xlmr-large-76L_script")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Davlan/afro-xlmr-large-76L_script") model = AutoModelForMaskedLM.from_pretrained("Davlan/afro-xlmr-large-76L_script", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Davlan/afro-xlmr-large-76L_script: direct link, hf CLI and curl.
- Browser
- Download file 18.6 MB
-
https://huggingface.co/Davlan/afro-xlmr-large-76L_script/resolve/main/tokenizer.json
- Command line
-
hf download hf://Davlan/afro-xlmr-large-76L_script/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Davlan/afro-xlmr-large-76L_script/resolve/main/tokenizer.json
18.6 MB
- Xet hash:
- 59b3cd94370fda26b543fa80f362fda4ba53321b94e303cb5fd19bcff6198515
- Size of remote file:
- 18.6 MB
- SHA256:
- ee4594336579b9e6f28157a3c5bd49c36454c17e968171fca3f8eaaae17d7515
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