Instructions to use Pyke/1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pyke/1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Pyke/1")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Pyke/1") model = AutoModel.from_pretrained("Pyke/1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d00209cb887768e8405cc6211fd2faa4838afccf3ccee377de4fc40a5ea988ad
- Size of remote file:
- 183 kB
- SHA256:
- 82e917a3fb467e13bb271bbb72c8abdb6e57f30aaa49b9e199019563aaedc384
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.