Instructions to use facebook/xmod-base-30-195k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/xmod-base-30-195k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="facebook/xmod-base-30-195k")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("facebook/xmod-base-30-195k") model = AutoModelForMaskedLM.from_pretrained("facebook/xmod-base-30-195k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/xmod-base-30-195k: direct link, hf CLI and curl.
- Browser
- Download file 1.96 GB
-
https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/xmod-base-30-195k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/pytorch_model.bin
1.96 GB
- Xet hash:
- 6ae5ea003566bf7f5e86310a0d44b035725f2c7cbc817e566732c9ddf45e73f3
- Size of remote file:
- 1.96 GB
- SHA256:
- a4fd0896581e15f0906be188f65107c62bec47b6b53158ac133af478bd114103
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