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
Download config_sentence_transformers.json from remodlai/nova-embeddings-v1: direct link, hf CLI and curl.
- Browser
- Download file 274 Bytes
-
https://huggingface.co/remodlai/nova-embeddings-v1/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://remodlai/nova-embeddings-v1/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/remodlai/nova-embeddings-v1/resolve/main/config_sentence_transformers.json
274 Bytes
- Xet hash:
- 450ae0b1ef7438d55234f6598c0e5a20f6d3f9f00574e1205d38ab74614e3a1a
- Size of remote file:
- 274 Bytes
- SHA256:
- 1eee316c1ced66356d6472a0f3e2ff28084e8a693cbb2bb758ed98cc3f20ba22
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