Instructions to use hf-internal-testing/tiny-random-nllb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-nllb with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-nllb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/decoder_model.onnx from hf-internal-testing/tiny-random-nllb: direct link, hf CLI and curl.
- Browser
- Download file 8.33 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-nllb/resolve/refs%2Fpr%2F1/onnx/decoder_model.onnx
- Command line
-
hf download hf://hf-internal-testing/tiny-random-nllb@refs/pr/1/onnx/decoder_model.onnx
-
curl -L -o decoder_model.onnx https://huggingface.co/hf-internal-testing/tiny-random-nllb/resolve/refs%2Fpr%2F1/onnx/decoder_model.onnx
8.33 MB
- Xet hash:
- bb5037e6cf068756cd372eb7fcba6e11ff8496d460144cdbeec6babdcde7443b
- Size of remote file:
- 8.33 MB
- SHA256:
- 4734121ecf35e6a6be8ba7e161b7e67f90c85096530e0c97e95e2daf72aa3e48
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.