Instructions to use minkhantycc/nlbb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use minkhantycc/nlbb with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-1.3B") model = PeftModel.from_pretrained(base_model, "minkhantycc/nlbb") - Transformers
How to use minkhantycc/nlbb with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("minkhantycc/nlbb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from minkhantycc/nlbb: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/minkhantycc/nlbb/resolve/main/tokenizer.json
- Command line
-
hf download hf://minkhantycc/nlbb/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/minkhantycc/nlbb/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- 769ae95eb8b8acefcf21d9486898eb341abe9e4ce2bdc12eeb1d8723aa3b4663
- Size of remote file:
- 32.2 MB
- SHA256:
- 1e799c7625f61747ce07590d230019ba91d04d23aec86a840cb0972ec21582db
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