Instructions to use Rekin226/nllb-600M-moore-lora-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Rekin226/nllb-600M-moore-lora-v0 with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-distilled-600M") model = PeftModel.from_pretrained(base_model, "Rekin226/nllb-600M-moore-lora-v0") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Rekin226/nllb-600M-moore-lora-v0: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/Rekin226/nllb-600M-moore-lora-v0/resolve/main/tokenizer.json
- Command line
-
hf download hf://Rekin226/nllb-600M-moore-lora-v0/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Rekin226/nllb-600M-moore-lora-v0/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- 655266d0d424ad17a22653c5437f69e3c87b9c5aaa49adc27e985e93a4e01e23
- Size of remote file:
- 32.2 MB
- SHA256:
- c3731d02d92ecf8827ba0a347be2b3cbb71cdbb46ba9fa4e2cbedd62f987bcff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.