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# RADAR: An Expert-Level Generalist AI for Abdominal CT Diagnosis

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Ultra-fast extraction of predefined clinical variables from free-text clinical notes.

# RADAR: An Expert-Level Generalist AI for Abdominal CT Diagnosis

Fx-Bio-0913 is a biomedical reasoning large language model post-trained on DeepSeek-V4-Flash, developed by The Endless Frontier lab. It is specialized for biological and biomedical research tasks — including gene-function puzzles, experimental reasoning, and multi-step evidence integration —…

!PIVOT overview

This model card provides an overview of the intended use of the ESMC SAE models and examples of how to access them, but it does not have a specific model or model weights. To access each SAE model collection, use the links below:

The ESMC scaling-study checkpoints are being released to support reproducibility of the findings in our paper, please refer to the paper and github for details. Please use the ESMC model for research work. ESMC is a state-of-the-art protein language model trained on billions of protein sequences…

The ESMC scaling-study checkpoints are being released to support reproducibility of the findings in our paper, please refer to the paper and github for details. Please use the ESMC model for research work. ESMC is a state-of-the-art protein language model trained on billions of protein sequences…

The ESMC scaling-study checkpoints are being released to support reproducibility of the findings in our paper, please refer to the paper and github for details. Please use the ESMC model for research work. ESMC is a state-of-the-art protein language model trained on billions of protein sequences…

ESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein…

ESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein…

ESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein…

ESMFold2 is a state-of-the-art model for protein structure prediction and design that defines a new frontier for speed and accuracy. The model predicts high-resolution, all-atom 3D protein structures directly from amino acid sequences, with optional multiple sequence alignment (MSA) input for…

ESMFold2 is a state-of-the-art model for protein structure prediction and design that defines a new frontier for speed and accuracy. The model predicts high-resolution, all-atom 3D protein structures directly from amino acid sequences, with optional multiple sequence alignment (MSA) input for…

Evo2-7B (Transformers port)

Evo2-1B-Base (Transformers port)

This bundle contains standardized CSV files and a Jupyter sample notebook for RMMol frozen-embedding examples across Biophysics, Physiological, Physical Chemistry, and Quantum Mechanics.

Machine-learned orbital-free density functional theory

CycleGAN generators that synthesise Ki-67 and pHH3 immunohistochemistry (IHC) appearance from H&E histopathology tiles of triple-negative breast cancer (TNBC).

!Benchmark card: Hertz 0.7F vs same-size models

# Geneformer Geneformer is a foundational transformer model pretrained on a large-scale corpus of human single cell transcriptomes to enable context-aware predictions in settings with limited data in network biology.

ONNX conversions of the existing RxnScribe, MolScribe and English EasyOCR checkpoints. This is a community conversion, not a newly trained model or an upstream release. Use the matching RxnScribe feature branch and its RxnScribeONNX interface. PyTorch is needed for export, not inference.

- Project page - Try Packora (live demo) - Paper - Code - Dataset manifests - Hugging Face collection

Winnow recalibrates confidence scores and provides FDR control for de novo peptide sequencing (DNS) workflows. This repository hosts a pretrained, general-purpose calibrator that maps raw InstaNovo model confidences and complementary features (mass error, retention time, beam features, fragment…

Winnow recalibrates confidence scores and provides FDR control for de novo peptide sequencing (DNS) workflows. This repository hosts a calibrator trained on the HeLa Single Shot dataset as referenced in our paper: De novo peptide sequencing rescoring and FDR estimation with Winnow.

> ⚠️ 重要：本仓库的 adapter 历史上因 PeftModel.frompretrained 双重包装导致 key 嵌套错误。 > 旧版本里 PeftModel.frompretrained 加载会"Found missing adapter keys"并静默丢弃全部权重， > 模型实际退化为 base Qwen2.5-3B-Instruct。 > 现在本仓库的 adapter_model.safetensors 已重新打包为标准深度 8（504/504 keys 命中），可被正确加载。 > 验证方式：见 shikunpunk/ask-dao-v0.3 仓库里 "Holdout…

知识发现机器 —— 从生物医学论文推断「作者没有明说」的开放科学问题

See the upstream model card for full details, training data and citation.

L1-30B-A5B is the Korean-locale medical foundation model from Lunit and Lunit Consortium. It is the 30B member of the L1 family, post-trained directly from Gravity-30B-A5B-Base, a sparse Mixture-of-Experts model developed by Trillion Labs and the Lunit Consortium.

### Model Overview TabPFN-3.5 is a transformer-based foundation model that uses in-context learning to solve tabular prediction problems in a forward pass. One checkpoint serves both classification and regression. Inference code can be found at https://github.com/PriorLabs/TabPFN.

💻 Github | 📄 Report | 🚀 Demo

Compared to MolDet, our new MolDetv2 model leverages more manually annotated training data, with further optimizations specifically for reducing molecular false detections and improving bounding box regression, achieving stronger performance with a smaller model.

Drafter checkpoints for EvSpark: a small distilled drafter that accelerates single-stream Evo2 7B (StripedHyena2) generation while staying distributionally lossless.

Medical SAM3 is a foundation model for universal prompt-driven medical image segmentation, obtained by fully fine-tuning SAM3 on large-scale, heterogeneous 2D and 3D medical imaging datasets with paired segmentation masks and text prompts.

# ReLSO: A Transformer-based Model for Latent Space Optimization and Generation of Proteins - github repo

PhenoSeq is a Gaussian diffusion model that generates scGPT RNA-seq embeddings conditioned on ViT-L microscopy imaging features. Given fluorescence microscopy images of a cell or well, it predicts a 512-dimensional scGPT embedding representing the transcriptomic state of individual cells — enabling…

Senba is a source-anchored adaptation of MarS-FM (Valence Labs, ICLR 2026) for mdCATH backbone transitions at 450 K and one 50-frame lag. It is published as a validation-stage candidate together with the selection receipt, every comparison, and the preregistered protocols, so the claim below can be…

Ultra-fast neural inference of episodic positive selection in molecular sequences.

C2S-Scale-Gemma-2-27B (GGUF Q8_0)

> TomatoPGFM v0.1.0 release metadata. Verify the SHA-256 value after downloading > the inference artifact before loading it.

This repository provides the pretrained Protenix v2 model weights for protein structure prediction.

!SynthVision