Instructions to use AfriNLP/AfriNLLB-12enc-8dec-middle-548m-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AfriNLP/AfriNLLB-12enc-8dec-middle-548m-ft with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="AfriNLP/AfriNLLB-12enc-8dec-middle-548m-ft")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AfriNLP/AfriNLLB-12enc-8dec-middle-548m-ft") model = AutoModelForSeq2SeqLM.from_pretrained("AfriNLP/AfriNLLB-12enc-8dec-middle-548m-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AfriNLP/AfriNLLB-12enc-8dec-middle-548m-ft: direct link, hf CLI and curl.
- Browser
- Download file 5.82 kB
-
https://huggingface.co/AfriNLP/AfriNLLB-12enc-8dec-middle-548m-ft/resolve/main/training_args.bin
- Command line
-
hf download hf://AfriNLP/AfriNLLB-12enc-8dec-middle-548m-ft/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AfriNLP/AfriNLLB-12enc-8dec-middle-548m-ft/resolve/main/training_args.bin
5.82 kB
- Xet hash:
- a205e54a17151aa7f7199e951631f57f79c83da8aedd755a84879985e4d285ca
- Size of remote file:
- 5.82 kB
- SHA256:
- e98d08cf5016670dba9098cd8fde4836ba98159b61821a591fa8b757cba041c9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.