Instructions to use hf-internal-testing/tiny-random-SiglipTextModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SiglipTextModel with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SiglipTextModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-SiglipTextModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91b1092f8693acbd96a1fe5bc6799e9c48fd5260b3c89234e75d009fe6fe4578
- Size of remote file:
- 4.22 MB
- SHA256:
- ab4a9fe5f8f89f2be7ef0e2326a705eb596be0b7161aade7ec4c729ac8674ec5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.