Instructions to use djelia/bm-xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djelia/bm-xlm-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="djelia/bm-xlm-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("djelia/bm-xlm-roberta-base") model = AutoModelForMaskedLM.from_pretrained("djelia/bm-xlm-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from djelia/bm-xlm-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 17 MB
-
https://huggingface.co/djelia/bm-xlm-roberta-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://djelia/bm-xlm-roberta-base/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/djelia/bm-xlm-roberta-base/resolve/main/tokenizer.json
17 MB
- Xet hash:
- cfe5587efea032fc180d43c01da6965cfe533660209a53bade96692e46512728
- Size of remote file:
- 17 MB
- SHA256:
- 37ca8233ebc6b0f98ce5f08c91345881e325717077d54a4a5c267e6361e3394e
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