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:
- c1c53b2ce944c73e32e1a63fea6973d545b303abb5d98ae7465f55a24dbdcf18
- Size of remote file:
- 726 Bytes
- SHA256:
- f4439f00d86669352d11321b568332bee8555b0b2a4bea1703e6d4b668810804
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