Feature Extraction
Transformers
Safetensors
embeddings
multimodal
vision
code
instruction-tuning
retrieval
text-matching
sentence-similarity
late-interaction
multi-vector
mteb
vidore
lora
adapter
nova
runtime-instructions
Eval Results (legacy)
Instructions to use remodlai/nova-embeddings-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use remodlai/nova-embeddings-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="remodlai/nova-embeddings-v1")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("remodlai/nova-embeddings-v1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3ee3f5aa0050a12d1b67339c32e1b3e4de90cdc2eab639bf978efd28a2fda3c
- Size of remote file:
- 20.3 kB
- SHA256:
- 304bc4d3d620c30be991b788fc0e5c3176495a404a6119d11dbc3c298d5ad575
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