Instructions to use malteos/specter-wol with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malteos/specter-wol with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="malteos/specter-wol")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("malteos/specter-wol") model = AutoModel.from_pretrained("malteos/specter-wol", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d12b6022bf34b80c0e3db4cc70f983e52e326bc08fe9f86034c0c6c9f9f2e9b
- Size of remote file:
- 440 MB
- SHA256:
- 5cc9d52d28b1d1335b3dc367eac35316ca875344dce5cbb71419b98ac575e9db
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.