Instructions to use FacebookAI/xlm-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/xlm-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FacebookAI/xlm-roberta-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FacebookAI/xlm-roberta-large") model = AutoModelForMaskedLM.from_pretrained("FacebookAI/xlm-roberta-large", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from FacebookAI/xlm-roberta-large: direct link, hf CLI and curl.
- Browser
- Download file 2.24 GB
-
https://huggingface.co/FacebookAI/xlm-roberta-large/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://FacebookAI/xlm-roberta-large/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/FacebookAI/xlm-roberta-large/resolve/main/flax_model.msgpack
2.24 GB
- Xet hash:
- 1cef5524c3d55857586cb31f6558abade342827dc03e9575005539d3f7547306
- Size of remote file:
- 2.24 GB
- SHA256:
- 96d19a73ca044be7c23518d2d23154eb0a1e6fb301d3b086e2d80bdfff1391ce
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