Instructions to use hf-internal-testing/tiny-random-TvltModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-TvltModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-TvltModel")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-TvltModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76b39c8956f7a4603f9192f25a3d9e27d202c93c43a0a07ff52d7b443f4a3be8
- Size of remote file:
- 5 MB
- SHA256:
- 020f1aeed5284611d0753b7023900ff0bb78e7c2ada1442dbed221b247fe9380
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.