Instructions to use Davlan/afro-xlmr-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/afro-xlmr-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Davlan/afro-xlmr-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Davlan/afro-xlmr-base") model = AutoModelForMaskedLM.from_pretrained("Davlan/afro-xlmr-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model (#3)
- Adding `safetensors` variant of this model (3da2872548c959379a8c799bf1a4a966ba391e07) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>25f2729 -
Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (9e6923306ac8c7b0f63d47123ced602abf30e8fe) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>b924e9a
-
Update README.md
ebac314
-
Update README.md
4574a44 -
Update README.md
8dacb5f
-
Update README.md
5ad5c22
-
Update README.md
b521433
-
Update README.md
8594203
-
Update README.md
bbe2118
-
Update README.md
bfba0ed -
Update README.md
e308d95 -
Update README.md
294eebd
-
Upload training_args.bin with git-lfs
97a0751 -
Upload tokenizer_config.json
88353a2 -
Upload tokenizer.json
516b806 -
Upload special_tokens_map.json
4782945 -
Upload sentencepiece.bpe.model with git-lfs
f6ec12b -
Upload README.md
1f36f73 -
Upload pytorch_model.bin with git-lfs
2427c83 -
Upload config.json
f75af36 -
initial commit
8102aaf