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 training_args.bin from benjamin/roberta-base-wechsel-swahili: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/benjamin/roberta-base-wechsel-swahili/resolve/main/training_args.bin
- Command line
-
hf download hf://benjamin/roberta-base-wechsel-swahili/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/benjamin/roberta-base-wechsel-swahili/resolve/main/training_args.bin
2.93 kB
- Xet hash:
- 591fdc334b9bfab39f3ac6163d6f2bc9fe781b0a714a36905f337607166d5be5
- Size of remote file:
- 2.93 kB
- SHA256:
- ca12d2a19aa3d165d7f3597ff915be7204109ca827e88a9a84ff9924e06c8c65
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