Feature Extraction
Transformers
PyTorch
milco
sparse-retrieval
multilingual
learned-sparse
cross-lingual
custom_code
Instructions to use omai-research/milco-650m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omai-research/milco-650m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="omai-research/milco-650m", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("omai-research/milco-650m", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened about 1 month ago
by
SFconvertbot