Instructions to use benjamin/roberta-base-wechsel-swahili with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benjamin/roberta-base-wechsel-swahili with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="benjamin/roberta-base-wechsel-swahili")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("benjamin/roberta-base-wechsel-swahili") model = AutoModelForMaskedLM.from_pretrained("benjamin/roberta-base-wechsel-swahili", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from benjamin/roberta-base-wechsel-swahili: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/benjamin/roberta-base-wechsel-swahili/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://benjamin/roberta-base-wechsel-swahili/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/benjamin/roberta-base-wechsel-swahili/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 601264882ef7ae1ba954a37ba1a47428fba56e52ea2b6c7ffe1562bb048d06f8
- Size of remote file:
- 499 MB
- SHA256:
- 1512d8b85daf4fe70f6380af7000bd844439dc84a6b4ceee07f90b3c0fd7aa0e
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