Instructions to use potemin/coencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use potemin/coencoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="potemin/coencoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("potemin/coencoder") model = AutoModel.from_pretrained("potemin/coencoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ff3d18dbedca51d206ade372a216178259775f6af1420ff3e013096f1436059
- Size of remote file:
- 117 MB
- SHA256:
- 981d1a44e242213128e5c90770624009b8fa2db8508f3be1d7284e092d0d4abb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.