Instructions to use allenai/specter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/specter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="allenai/specter")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("allenai/specter") model = AutoModel.from_pretrained("allenai/specter") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0f6e5cafa9ee224b21c69e2a48a80f6a4a8b68b3af827a69a0164cb44f4dad8
- Size of remote file:
- 440 MB
- SHA256:
- 6d84dc0bb064c651956611b39ed13a043d88ee7a1dd1239913ac06840a7fa53c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.