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:
# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-NllbMoeForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94bae257f362da3137a413700f10549517cc0ced77e44cd2fbbd04f2087a7292
- Size of remote file:
- 16.6 MB
- SHA256:
- 8d6e10c12bbb8e53d31345b6fb9208569454ec04ba7bc20c9184bebfcf6b8a55
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.