Instructions to use hf-internal-testing/tiny-random-NllbMoeForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-NllbMoeForConditionalGeneration with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-NllbMoeForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from hf-internal-testing/tiny-random-NllbMoeForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 17.3 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-NllbMoeForConditionalGeneration/resolve/4cd8b68ab43645ebdad05e5779a88f5fac59a142/tokenizer.json
- Command line
-
hf download hf://hf-internal-testing/tiny-random-NllbMoeForConditionalGeneration@4cd8b68ab43645ebdad05e5779a88f5fac59a142/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/hf-internal-testing/tiny-random-NllbMoeForConditionalGeneration/resolve/4cd8b68ab43645ebdad05e5779a88f5fac59a142/tokenizer.json
17.3 MB
- Xet hash:
- 6001776ccf5d77841d8a555e0554adaeb3e5516aea30f8f3c1bfe15c754ceadf
- Size of remote file:
- 17.3 MB
- SHA256:
- 61d9fa2a120c698d4811baf67ead672fbed532a54c6e1ce4bd7efea26d327429
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.