Instructions to use FacebookAI/xlm-clm-ende-1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/xlm-clm-ende-1024 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FacebookAI/xlm-clm-ende-1024")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FacebookAI/xlm-clm-ende-1024") model = AutoModelForMaskedLM.from_pretrained("FacebookAI/xlm-clm-ende-1024", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from FacebookAI/xlm-clm-ende-1024: direct link, hf CLI and curl.
- Browser
- Download file 835 MB
-
https://huggingface.co/FacebookAI/xlm-clm-ende-1024/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://FacebookAI/xlm-clm-ende-1024/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/FacebookAI/xlm-clm-ende-1024/resolve/main/pytorch_model.bin
835 MB
- Xet hash:
- dc93de7bd5676ded51805c3a02c10156516ef93616f894aae234b32037ba9854
- Size of remote file:
- 835 MB
- SHA256:
- 1a1c5fbe53ba1c17162e84f1dd576d1ce41a57d053317ca0649f60fe19757c83
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.