Instructions to use hf-internal-testing/tiny-random-onnx-mt5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-onnx-mt5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-onnx-mt5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-onnx-mt5") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-onnx-mt5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/encoder_model.onnx from hf-internal-testing/tiny-random-onnx-mt5: direct link, hf CLI and curl.
- Browser
- Download file 16.4 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-onnx-mt5/resolve/main/onnx/encoder_model.onnx
- Command line
-
hf download hf://hf-internal-testing/tiny-random-onnx-mt5/onnx/encoder_model.onnx
-
curl -L -o encoder_model.onnx https://huggingface.co/hf-internal-testing/tiny-random-onnx-mt5/resolve/main/onnx/encoder_model.onnx
16.4 MB
- Xet hash:
- c4cf9ad9fc69ebc7e0016743d6fab08c1b9e5f8828e44c15db12bc0aac17e8a4
- Size of remote file:
- 16.4 MB
- SHA256:
- 37c3da5b4ee2a873f2b7fc83e65b1c7c980227e933b9c68ca821fd8221bcb86b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.