Explore
Models
Blueprints
GPUs
Docs
⌘K
Ctrl+K
?
Login
9 results for
Filters
Models (9)
Blueprints (5)
Other (0)
Sort By
score:DESC
Best Match
NVIDIA
nv-embedqa-e5-v5
English text embedding model for question-answering retrieval.
Model
Embedding
+4
3.14M
7mo
NVIDIA
llama-3.2-nemoretriever-1b-vlm-embed-v1
Multimodal question-answer retrieval representing user queries as text and documents as images.
Model
nemo retriever
+3
270K
8mo
NVIDIA
llama-3.2-nv-rerankqa-1b-v2
Fine-tuned reranking model for multilingual, cross-lingual text question-answering retrieval, with long context support.
Model
nemo retriever
+2
166K
7mo
NVIDIA
llama-3_2-nemoretriever-300m-embed-v1
Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
Model
Retrieval Augmented Generation
+2
90.75K
7mo
NVIDIA
llama-3_2-nemoretriever-300m-embed-v2
Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
Model
Retrieval Augmented Generation
+2
122K
5mo
NVIDIA
llama-nemotron-embed-1b-v2
Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
Model
Retrieval Augmented Generation
+2
327K
1w
NVIDIA
llama-nemotron-embed-vl-1b-v2
Multimodal question-answer retrieval representing user queries as text and documents as images.
Model
nemo retriever
+3
818K
4w
NVIDIA
llama-3.2-nv-embedqa-1b-v2
Multilingual and cross-lingual text question-answering retrieval with long context support and optimized data storage efficiency.
Model
nemo retriever
+3
7.11M
7mo
NVIDIA
nv-embedcode-7b-v1
The NV-EmbedCode model is a 7B Mistral-based embedding model optimized for code retrieval, supporting text, code, and hybrid queries.
Model
nemo retriever
+2
263K
9mo
Items per page
24
1
1
of 1 pages
