Instructions to use FacebookAI/xlm-mlm-enro-1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/xlm-mlm-enro-1024 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FacebookAI/xlm-mlm-enro-1024")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FacebookAI/xlm-mlm-enro-1024") model = AutoModelForMaskedLM.from_pretrained("FacebookAI/xlm-mlm-enro-1024", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1250edc3c9541515d804991bdc6beb8a182c5c8841dab35b46d4411654a4764d
- Size of remote file:
- 834 MB
- SHA256:
- 35960eab1b2869e9198ac2ec7ceea35eaa43aa9630dfee782675e5e753a23430
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.