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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8444ff423aef2d1e21f99ee68398cee139206e7e5c5d2d4291ef60f1942b8527
- Size of remote file:
- 126 Bytes
- SHA256:
- 4be8e7b43a811255a415e39b11c9b78a3a267120e20dd198774b1a14dcc5ea86
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