Instructions to use stonesstones/vae_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stonesstones/vae_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="stonesstones/vae_test", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("stonesstones/vae_test", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from stonesstones/vae_test: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/stonesstones/vae_test/resolve/main/training_args.bin
- Command line
-
hf download hf://stonesstones/vae_test/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/stonesstones/vae_test/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 7488acf71687a59d1fe9b1f7e5d19aae5a41bd1ad2bf2338225bdc7ad388eec8
- Size of remote file:
- 5.37 kB
- SHA256:
- f8faac91036e8ec73700214fe8baff21d52da005b8df0a5bb0395bd50f3f1c8b
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