Instructions to use facebook/xmod-base-60-265k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/xmod-base-60-265k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="facebook/xmod-base-60-265k")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("facebook/xmod-base-60-265k") model = AutoModelForMaskedLM.from_pretrained("facebook/xmod-base-60-265k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d013ee37341d2a16039b57fe594529fe843f1c1bdeb463ad8c9e6bf942c1beaf
- Size of remote file:
- 2.82 GB
- SHA256:
- ee8121b0ebd6a13b8d2eb8d7ccb82276a00d8757334d2fc293179c20928b62e8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.