Instructions to use hf-internal-testing/tiny-random-m2m_100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-m2m_100 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-m2m_100", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/decoder_model.onnx from hf-internal-testing/tiny-random-m2m_100: direct link, hf CLI and curl.
- Browser
- Download file 8.31 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-m2m_100/resolve/refs%2Fpr%2F2/onnx/decoder_model.onnx
- Command line
-
hf download hf://hf-internal-testing/tiny-random-m2m_100@refs/pr/2/onnx/decoder_model.onnx
-
curl -L -o decoder_model.onnx https://huggingface.co/hf-internal-testing/tiny-random-m2m_100/resolve/refs%2Fpr%2F2/onnx/decoder_model.onnx
8.31 MB
- Xet hash:
- 046f68d13fd1bc0d03b8bab9eb193caa9aaffc755408a59093f0958e5c2b4c08
- Size of remote file:
- 8.31 MB
- SHA256:
- 0a25bee6f700108d72bc5fd77ad33b3fdad3c0c104ccd8af6027493742729fd3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.