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
metadata
language:
- multilingual
- af
- am
- ar
- be
- bn
- ca
- cs
- cy
- da
- en
- eo
- et
- eu
- fa
- fi
- fr
- ga
- gl
- gu
- ha
- hi
- hr
- hu
- hy
- id
- is
- it
- ka
- ko
- ku
- la
- lt
- lv
- mk
- ml
- mn
- ms
- ne
- nl
- 'no'
- pl
- ps
- pt
- ro
- ru
- sa
- sd
- si
- sk
- sl
- so
- sq
- sr
- sv
- sw
- ta
- te
- th
- tl
- vi
license: mit
An X-MOD model of size base trained on 60 languages for 265k update steps.
See https://huggingface.co/jvamvas/xmod-base for details.