Instructions to use FacebookAI/xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/xlm-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FacebookAI/xlm-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FacebookAI/xlm-roberta-base") model = AutoModelForMaskedLM.from_pretrained("FacebookAI/xlm-roberta-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from FacebookAI/xlm-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/FacebookAI/xlm-roberta-base/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://FacebookAI/xlm-roberta-base/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/FacebookAI/xlm-roberta-base/resolve/main/flax_model.msgpack
1.11 GB
- Xet hash:
- 93c5ca39cf3578fd11a38fd508f724ef05862709100bc53e2ffeedd04f08de39
- Size of remote file:
- 1.11 GB
- SHA256:
- 311b6941e02128b01c6a429f55b47b351a86fe53e6802774d87696bcbc465992
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