Sentence Similarity
sentence-transformers
Safetensors
Transformers
multilingual
llama_nemotron_vl
feature-extraction
retrieval
visual document retrieval
vlm embedding
page image embedding
text embedding
semantic search
question-answering retrieval
rag
custom_code
Instructions to use nvidia/llama-nemotron-embed-vl-1b-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nvidia/llama-nemotron-embed-vl-1b-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nvidia/llama-nemotron-embed-vl-1b-v2", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use nvidia/llama-nemotron-embed-vl-1b-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/llama-nemotron-embed-vl-1b-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Tom Aarsen commited on
Commit ·
4fb4c43
1
Parent(s): e08714e
Use transformers load_image as the repository's load_image doesn't have user-agent
Browse files
README.md
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@@ -135,6 +135,7 @@ This model supports **text**, **image**, and **image+text** embedding with Sente
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```python
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from sentence_transformers import SentenceTransformer
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model = SentenceTransformer("nvidia/llama-nemotron-embed-vl-1b-v2", trust_remote_code=True)
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]
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# Images can be URLs, file paths, or PIL Images
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images = [
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"https://developer.download.nvidia.com/images/isaac/nvidia-isaac-lab-1920x1080.jpg",
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"https://blogs.nvidia.com/wp-content/uploads/2018/01/automotive-key-visual-corp-blog-level4-av-og-1280x680-1.png",
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"https://developer-blogs.nvidia.com/wp-content/uploads/2025/02/hc-press-evo2-nim-25-featured-b.jpg",
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]
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# Text-only encoding
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```python
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from sentence_transformers import SentenceTransformer
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from transformers.image_utils import load_image
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model = SentenceTransformer("nvidia/llama-nemotron-embed-vl-1b-v2", trust_remote_code=True)
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]
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# Images can be URLs, file paths, or PIL Images
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images = [
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load_image("https://developer.download.nvidia.com/images/isaac/nvidia-isaac-lab-1920x1080.jpg"),
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load_image("https://blogs.nvidia.com/wp-content/uploads/2018/01/automotive-key-visual-corp-blog-level4-av-og-1280x680-1.png"),
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load_image("https://developer-blogs.nvidia.com/wp-content/uploads/2025/02/hc-press-evo2-nim-25-featured-b.jpg"),
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]
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# Text-only encoding
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