Instructions to use scales-okn/docket-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scales-okn/docket-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="scales-okn/docket-encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("scales-okn/docket-encoder") model = AutoModel.from_pretrained("scales-okn/docket-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd1edf6626421acdefe2bcfa2858a18ff26b67d75e806636cb09a39ebe79d413
- Size of remote file:
- 3.18 kB
- SHA256:
- f3c07d6002877baa8b565a5e7196ab7927f7d211da1c15f0c1f1c98849cb11bc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.