Instructions to use hf-internal-testing/tiny-random-ErnieMModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ErnieMModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-ErnieMModel")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ErnieMModel", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a88cd1ea831b3c866b2071528690c99e8cd02dabf7f73e7a24d838d81042acb
- Size of remote file:
- 32.2 MB
- SHA256:
- 57ee0bf41a63f30d0f7ef89e7f2b97faacf924771de382d0e02cb6c6ba895a5c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.