Instructions to use DLight1551/JSH_0624 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DLight1551/JSH_0624 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DLight1551/JSH_0624", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DLight1551/JSH_0624", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 798e9df73a36c016cf6206ef95b0467a383662bc5e12e6fe20f481caabe96b9a
- Size of remote file:
- 6.01 kB
- SHA256:
- 9288daff0c083b1a04d7bcb7162736f8573cf89f15cf6320d94e7f169558f28f
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