Fill-Mask
Transformers
PyTorch
Safetensors
Swahili
bert
masked-language-modeling
swahili
low-resource-languages
africa
Instructions to use eolang/sw-fillmask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eolang/sw-fillmask with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="eolang/sw-fillmask")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("eolang/sw-fillmask") model = AutoModelForMaskedLM.from_pretrained("eolang/sw-fillmask", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 26450b21f4b3a18c2873f4f340308eac3e43f12166903956ba1cef7e91f663ae
- Size of remote file:
- 438 MB
- SHA256:
- 82bceb9bda2c2d046f66824d16c9aac4e5237a076224e048b202ed2eb2b9c760
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