Models#
Attention
The .models is already deprecated, please import from lazyslide_models instead.
List all available models. |
Vision models#
GitHub Paper Params: 27.5M 768 features FLOPs: 8.99G AGPL-3.0 [Wang et al., 2024] Clinical Histopathology Imaging Evaluation Foundation (CHIEF) |
|
GitHub Paper Params: 27.5M 768 features FLOPs: 8.99G GPL-3.0 [Wang et al., 2022] Transformer-based unsupervised contrastive learning for histopathological image classification |
|
🤗Hugging Face GitHub Paper Params: 303M 1024 features FLOPs: 155.53G CC BY-NC-ND 4.0 [Ma et al., 2025] Generalizable Pathology Foundation Model |
|
🤗Hugging Face GitHub Paper Params: 1.1B 4608 features GenBio AI Community License [Kapse et al., 2026] A state-of-the-art histopathology foundation model trained with JEDI (JEPA + DINO) |
|
🤗Hugging Face GitHub Paper Params: 1.13B 1536 features Apache 2.0 with conditions [Xu et al., 2024] A whole-slide foundation model for digital pathology |
|
🤗Hugging Face GitHub Paper Params: 85.7M 1536 features FLOPs: 44.57G CC-BY-NC-ND-4.0 [Filiot et al., 2025] A distilled version of H-optimus-0 |
|
🤗Hugging Face GitHub Params: 1.13B 1536 features Apache 2.0 [Saillard et al., 2024] Vision foundation model |
|
🤗Hugging Face GitHub Params: 1.13B 1536 features FLOPs: 591.61G CC-BY-NC-ND-4.0 [Bioptimus, 2025] Vision foundation model |
|
🤗Hugging Face GitHub Paper Params: 85.7M 768 features FLOPs: 47.08G Apache 2.0 [Nechaev et al., 2024] A family of foundational vision transformers for pathology |
|
🤗Hugging Face GitHub Paper Params: 303.7M 1024 features FLOPs: 164.85G Apache 2.0 [Nechaev et al., 2024] A family of foundational vision transformers for pathology |
|
🤗Hugging Face GitHub Paper Params: 21.7M 384 features lunit-non-commercial [Kang et al., 2023] Benchmarking Self-Supervised Learning on Diverse Pathology Datasets |
|
🤗Hugging Face GitHub Paper Params: 21.1M 384 features lunit-non-commercial [Kang et al., 2023] Benchmarking Self-Supervised Learning on Diverse Pathology Datasets |
|
🤗Hugging Face GitHub Paper Params: 23.6M 2048 features lunit-non-commercial [Kang et al., 2023] Benchmarking Self-Supervised Learning on Diverse Pathology Datasets |
|
🤗Hugging Face GitHub Paper Params: 23.6M 2048 features lunit-non-commercial [Kang et al., 2023] Benchmarking Self-Supervised Learning on Diverse Pathology Datasets |
|
🤗Hugging Face GitHub Paper Params: 23.6M 2048 features lunit-non-commercial [Kang et al., 2023] Benchmarking Self-Supervised Learning on Diverse Pathology Datasets |
|
🤗Hugging Face GitHub Paper Params: 1.14B 3072 features FLOPs: 582.55G MIT [Karasikov et al., 2025] Training state-of-the-art pathology foundation models with orders of magnitude less data |
|
🤗Hugging Face GitHub Params: 1.1B 1536 features Apache 2.0 [Kaplan et al., 2025] Open replication of Midnight, a state-of-the-art pathology foundation model trained on 12K slides |
|
🤗Hugging Face GitHub CC-BY-NC-ND-4.0 [Yan et al., 2025] Foundation Model for Computational Pathology |
|
🤗Hugging Face GitHub Paper Params: 85.8M 768 features FLOPs: 33.70G Owkin non-commercial license [Filiot et al., 2023] Scaling self-Supervised Learning for histopathology with Masked Image Modeling |
|
🤗Hugging Face GitHub Paper Params: 303.4M 1024 features FLOPs: 119.29G Owkin non-commercial license [Filiot et al., 2024] A large and public feature extractor for biomarker prediction |
|
🤗Hugging Face GitHub Paper Params: 303.4M 1024 features CC-BY-NC-ND-4.0 [Chen et al., 2024] General-purpose self-supervised model for pathology |
|
🤗Hugging Face GitHub Paper Params: 681.4M 1536 features CC-BY-NC-ND-4.0 [Chen et al., 2024] An improved version of UNI |
|
🤗Hugging Face Paper Params: 631.2M 2560 features FLOPs: 323.93G Apache 2.0 [Vorontsov et al., 2024] A foundation model for clinical-grade computational pathology and rare cancers detection |
|
🤗Hugging Face Paper Params: 631.2M 2560 features FLOPs: 328.97G CC-BY-NC-ND-4.0 [Zimmermann et al., 2024] Scaling self-supervised mixed magnification models in pathology |
Multimodal models#
🤗Hugging Face GitHub Paper 512 features MIT [Zhang et al., 2024] A biomedical VLP foundation model pretrained on PMC-15M image-text pairs |
|
🤗Hugging Face GitHub Paper Params: 395.2M 512 features FLOPs: 35.08G CC-BY-NC-ND-4.0 [Lu et al., 2024] CONtrastive learning from Captions for Histopathology (CONCH) |
|
🤗Hugging Face GitHub Paper Params: 675.2M 1024 features FLOPs: 382.13G CC-BY-NC-ND-4.0 [Xiang et al., 2025] A Vision-Language Foundation Model for Precision Oncology |
|
🤗Hugging Face GitHub Paper Params: 878M 1152 features health-ai-developer-foundations [Sellergren et al., 2025] MedSigLip is a variant of SigLip from Google for medical image analysis. |
|
🤗Hugging Face GitHub Paper Params: 638.5M FLOPs: 156.94G BSD-3-Clause [Chen et al., 2025] A visual-omics foundation model to bridge histopathology with spatial transcriptomics |
|
🤗Hugging Face GitHub Paper Params: 87.8M 512 features FLOPs: 8.73G Non-commercial [Huang et al., 2023] Pathology Language-Image Pretraining (PLIP) |
|
🤗Hugging Face Paper Params: 557.7M CC-BY-NC-ND-4.0 [Shaikovski et al., 2024] A multi-modal generative foundation model for slide-level histopathology, the Prism models encode slide-level embeddings from |
|
🤗Hugging Face GitHub Paper 512 features MIT [Ikezogwo et al., 2023] Quilt-1M: histopathology vision-language model trained on 1M image-text pairs |
|
🤗Hugging Face GitHub Paper 512 features MIT [Ikezogwo et al., 2023] Quilt-1M: histopathology vision-language model trained on 1M image-text pairs ViT-B/16 image tower with PubMedBERT text tower. |
|
🤗Hugging Face GitHub Paper 512 features MIT [Ikezogwo et al., 2023] Quilt-1M: histopathology vision-language model trained on 1M image-text pairs |
|
🤗Hugging Face GitHub Paper Params: 158.9M 768 features CC-BY-NC-ND-4.0 [Ding et al., 2024] Multimodal whole slide foundation model for pathology |
Segmentation models#
🤗Hugging Face GitHub Paper BSD-3-Clause [Stringer et al., 2021] Cell segmentation model |
|
GitHub Paper Params: 6.3M FLOPs: 4.63G CC-BY-NC-SA-4.0 [Weng et al., 2024] Artifact segmentation model from GrandQC |
|
GitHub Paper Params: 6.6M FLOPs: 8.46G CC-BY-NC-SA-4.0 [Weng et al., 2024] Tissue segmentation model from GrandQC |
|
🤗Hugging Face Params: 39.6M FLOPs: 62.61G CC-BY-NC-SA-4.0 DeepLabV3 model finetuned on HEST-1k and Acrobat for IHC/H&E tissue segmentation. |
|
🤗Hugging Face GitHub Paper Params: 47.9M FLOPs: 3.81T CC-BY-NC-ND-4.0 [Adjadj et al., 2025] Towards Comprehensive Cellular Characterisation of H&E slides |
|
GitHub Paper Params: 3.8M FLOPs: 27.55G Apache 2.0 [Goldsborough et al., 2024] An embedding-based instance segmentation algorithm optimized for accurate, efficient and portable cell segmentation. |
|
GitHub Paper Params: 47.9M FLOPs: 48.10G Apache 2.0; CC-BY-NC-SA-4.0 [Tommasino et al., 2024] Nuclei instance segmentation and classification |
|
GitHub Paper Params: 50.3M FLOPs: 44.94G GPL-3.0 [Haghighat et al., 2022] Tissue segmentation model from PathProfiler |
|
GitHub Paper FLOPs: 975.67G Apache 2.0 SAM model for image segmentation |
|
This is a base class for any models from segmentation models pytorch |
Tile prediction models#
GitHub Paper Params: 299 FLOPs: 1.53M Prosperity Public License 3.0.0 [Wang et al., 2020] High efficiency Focus Quality Assessment for digital pathology |
|
GitHub Paper Params: 11.2M FLOPs: 3.63G GPL-3.0 [Haghighat et al., 2022] Quality assessment of histology images |
|
🤗Hugging Face Params: 303.9M FLOPs: 164.85G CC BY-NC 4.0 Tile classification for breast |
|
🤗Hugging Face Params: 303.9M FLOPs: 164.85G CC BY-NC 4.0 Tile classification for colorectal |
|
🤗Hugging Face Params: 303.9M FLOPs: 164.85G CC BY-NC 4.0 Tile classification for skin |
|
🤗Hugging Face Params: 303.9M FLOPs: 164.85G CC BY-NC 4.0 Tile classification for thorax |
Slide encoder models#
🤗Hugging Face Paper Params: 557.7M CC-BY-NC-ND-4.0 [Shaikovski et al., 2024] A multi-modal generative foundation model for slide-level histopathology, the Prism models encode slide-level embeddings from |
|
🤗Hugging Face GitHub Paper Params: 158.9M 768 features CC-BY-NC-ND-4.0 [Ding et al., 2024] Multimodal whole slide foundation model for pathology |
|
GitHub Paper Params: 1.2M FLOPs: 131.28M AGPL-3.0 [Wang et al., 2024] Clinical Histopathology Imaging Evaluation Foundation (CHIEF) |
|
🤗Hugging Face GitHub Paper Apache 2.0 with conditions [Xu et al., 2024] A whole-slide foundation model for digital pathology |
|
🤗Hugging Face GitHub Paper Params: 3.2M FLOPs: 421.63M CC BY-NC-ND 4.0 [Jaume et al., 2024] Multistain Pretraining for Slide Representation Learning in Pathology |
|
🤗Hugging Face GitHub Paper Params: 85.77M 768 features CC-BY-NC-SA-4.0 [Kotp et al., 2026] A patient-first foundation model for computational pathology MOOZY slide and case encoder. |
Computer vision features#
Style transfer models#
GitHub Paper Params: 9M FLOPs: 52.88G PROV-GIGATIME LICENSE [Valanarasu et al., 2025] Multimodal AI generates virtual population for tumor microenvironment modeling |
|
GitHub Paper Params: 50M FLOPs: 17.37G CC-BY-NC-4.0 [Wu et al., 2025] AI generation of multiplex immunofluorescence staining from histopathology images |
Image generation models#
Base model class#
Base class for slide-level encoders. |
|