Instructions to use UBC-NLP/serengeti with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/serengeti with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="UBC-NLP/serengeti")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/serengeti") model = AutoModelForMaskedLM.from_pretrained("UBC-NLP/serengeti", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download serengati_languages.jpg from UBC-NLP/serengeti: direct link, hf CLI and curl.
- Browser
- Download file 249 kB
-
https://huggingface.co/UBC-NLP/serengeti/resolve/main/serengati_languages.jpg
- Command line
-
hf download hf://UBC-NLP/serengeti/serengati_languages.jpg
-
curl -L -o serengati_languages.jpg https://huggingface.co/UBC-NLP/serengeti/resolve/main/serengati_languages.jpg
249 kB
