Model reference · open weights
SigLIP-NaViT is an open-weight embedding model from DAMO-NLP-SG. SigLIP-NaViT (BF16) weighs 824 MB; the smallest configuration that runs it is RTX 3060 12 GB.
What it is
| Released by | DAMO-NLP-SG |
|---|---|
| Type | Embedding models |
| Task | Embeddings |
| Parameters (lead) | 412M |
| Runs with | transformers |
| Released | 2025-01-21 |
| Popularity | 4k downloads / month |
| Weights | 824 MB (SigLIP-NaViT (BF16), file size) |
| Licence | Licence not stated |
What it runs on
Weights 824 MB (file size) · overhead about 1.1 GB.
| Card | Runs | Counted memory |
|---|---|---|
| RTX 3060 12 GB | fits | 11.6 GB |
| RTX 4060 Ti 16 GB | fits | 15.4 GB |
| RTX 3090 24 GB | fits | 23.4 GB |
| RTX 4090 24 GB | fits | 23.4 GB |
| RTX 5090 32 GB | fits | 31.0 GB |
| L40S 48 GB | fits | 44.0 GB |
| A100 80 GB | fits | 78.2 GB |
| H100 80 GB | fits | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | fits | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | fits | 107 GB |
| H200 141 GB | fits | 138 GB |
| B200 180 GB | fits | 176 GB |
Estimates, not measurements: the weights are the build's file size. No cache grows with use; a batch of inputs needs working memory of its own. Counted memory is 92 % of what CUDA reports for the card.
From the model card
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
Use the code below to get started with the model.
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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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BibTeX:
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APA:
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Quoted from the model card on Hugging Face — the full card is behind the Hugging Face link above.