Instructions to use FacebookAI/xlm-clm-enfr-1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/xlm-clm-enfr-1024 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FacebookAI/xlm-clm-enfr-1024")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FacebookAI/xlm-clm-enfr-1024") model = AutoModelForMaskedLM.from_pretrained("FacebookAI/xlm-clm-enfr-1024", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from FacebookAI/xlm-clm-enfr-1024: direct link, hf CLI and curl.
- Browser
- Download file 830 MB
-
https://huggingface.co/FacebookAI/xlm-clm-enfr-1024/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://FacebookAI/xlm-clm-enfr-1024/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/FacebookAI/xlm-clm-enfr-1024/resolve/main/pytorch_model.bin
830 MB
- Xet hash:
- ad9fb634734b52d4f426e7275f33dd17053befa4af831d539401f26fc2009e6d
- Size of remote file:
- 830 MB
- SHA256:
- bb8e3a83d01a50f3a6a0c453a26984747cf44499c2d27ffd0d8415fddd900d66
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