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Heretic-abliterated version of Qwen/Qwen2.5-0.5B-Instruct for the Evolva drug discovery pipeline.

HantaBERT fine-tunes DNABERT-2 on hantavirus RNA sequences for three simultaneous classification tasks: species/lineage, host, and geographic origin. A single forward pass produces predictions for all three tasks along with a 768-dimensional embedding suitable for phylogenetic visualization.

For a convenient overview and download list, visit our model page for this model.

Xinghe1-9B (杏核) is a specialized large language model fine-tuned for the formalization, computational derivation, and clinical reasoning of Huangdi Neijing. It is based on the Qwen3.5-9B-Instruct architecture and trained using the V3 Double-Purity SFT dataset.

Pretrained LDARNet (~2M params) with learnable DNA tokenization (dynamic chunking + BiMamba-2).

Pretrained LDARNet (~110M params) with learnable DNA tokenization (dynamic chunking + BiMamba-2).

# Overview This is the CellHermes model, based on the LLaMA-3.1-8B-instruct architecture developed by Meta, fine-tuned using single-cell RNA sequencing (scRNA-seq) datasets from CellxGene and PPI network from BioGRID. CellHermes is an innovative framework for adapting existing large language models…

This repository contains Chemistry fine-tuned Qwen3-4B checkpoints from the local SciKnowEval-style generalization setup.

PlantGeneAnn is a plant genome foundation model that enables the prediction of various plant genomic elements at single-nucleotide resolution. The model is built upon the PlantBiMoE architecture with a 1D U-Net segmentation head, specifically designed for automated plant genome annotation.

33 lightweight, standalone models that predict discrete Alzheimer's-disease–related phenotypes (e.g. medication use, APOE genotype, vascular pathology, sex) from SomaScan plasma proteomics. The full list is in phenotypes.tsv.

69 lightweight, standalone models that predict continuous Alzheimer's-disease–related phenotypes (cognition, neuropathology burden, motor/functional measures, demographics, a genetic risk score, and longitudinal change) from SomaScan plasma proteomics.

This repository contains a drop-in, Hugging Face–compatible checkpoint converted from https://huggingface.co/microsoft/llava-med-v1.5-mistral-7b. You can load it with the exact same code you use for the original model—no extra conversion steps required.

👋 Join our LiGHT community. 📖 Check out the MeditronFO blog and MeditronFO preprint. 🔜 If you are a clinician join the MOOVE initiative here.

Sexo-FR is a French-language conversational language model that provides reliable, caring, and evidence-based sexual health information (information en santé sexuelle). It is part of a French public-health initiative whose goal is to make trustworthy sexual-health information more accessible to the…

👋 Join our LiGHT community. 📖 Check out the MeditronFO blog and MeditronFO preprint. 🔜 If you are a clinician join the MOOVE initiative here.

Gravity-bio-16B-A3B is a biology-focus midtrained model derived from Gravity-16B-A3B-Base. It uses the same sparse Mixture-of-Experts (MoE) architecture and tokenizer as Gravity-16B-A3B-Base, with additional midtraining for biological understanding on TheBioCollection corpus.

A lightweight plasma-protein aging clock that predicts chronological age from 85 unique inflammatory proteins measured by SomaScan (125 aptamers / SomaScan features). The model is a TabM† student distilled from a TabPFN v2 teacher, so it runs at inference without any TabPFN dependency (small,…

A lightweight plasma-protein aging clock that predicts chronological age from 92 Olink Inflammation-panel proteins. The model is a TabM† student distilled from a TabPFN v2 teacher, so it runs at inference without any TabPFN dependency (small, DUA-friendly artifacts).

Jolia is a 3D CT foundation model that encodes images into vector representations program. It encodes a whole 3D CT volume into:

Molexar-10M Base is the unconditional base model for Molexar, a unified multimodal molecular foundation model for drug design. It is trained as an autoregressive molecular language model over Fragment-SELFIES, a BRICS-fragment molecular language with validity-preserving decoding and…

Molexar-10M Omni is the universal multi-condition model for Molexar, a unified multimodal molecular foundation model for drug design. It starts from fairydance/molexar-10m-base and is supervised fine-tuned to generate Fragment-SELFIES molecules under scalar molecular-property,…

JEPA-based spatial-transcriptomics foundation model (TERRA). Code & docs: https://github.com/Lotfollahi-lab/terra

GRamma-12B is a 12-billion-parameter instruction-tuned language model specialized for the Greek medical domain. It is built on top of Gemma 3 12B Instruct and adapted through parameter-efficient fine-tuning on a collection of Greek and bilingual medical question-answering data.

Full weight-level fine-tuning of InstaDeepAI/nucleotide-transformer-v2-50m-multi-species for binary DNA sequence classification on two GenomicBenchmarks tasks. All parameters are updated rather than using LoRA or a frozen backbone, with a leakage-free train/validation/test protocol and multi-seed…

> Source code, training scripts, and inference utilities for this model: > github.com/NVIDIA-BioNeMo/KERMT > (v2.0 branch / v2.0.0 release tag)

QLoRA adapter for Llama-3.1-8B-Instruct, fine-tuned on PubMedQA for yes / no / maybe biomedical question answering (run5).

BioMatrix is a multimodal biological foundation model that natively integrates 1D sequences, 3D structures, and natural language for both molecules and proteins within a single decoder-only architecture.

A domain-adapted clinical LLM fine-tuned on synthetic Indian medical Q&A records using QLoRA (4-bit quantization) with Unsloth 2x speedup. Built to power the conversational AI layer.

This Hugging Face repository stores the official resources for RAMER (reaction-aware multimodal enzyme function representation model).

ProtGPT3-MSA is a multiple-sequence, homolog-conditioned autoregressive protein language model. It is part of the ProtGPT3 family, an open-source suite of promptable and aligned protein language models for protein sequence generation.

KAU-BioMedLLM is a research prototype for source-grounded biomedical variant interpretation. The current public release contains the LoRA adapter and documentation for a guarded report-generation system built around a curated biomedical evidence panel, citation enforcement, and abstention when…

Stack is a large-scale encoder-decoder foundation model for single-cell biology. It introduces a novel tabular attention architecture that enables both intra- and inter-cellular information flow, setting cell-by-gene matrix chunks as the basic input data unit.

ApeTokenizer-SMILES is an Atom Pair Encoding (APE) tokenizer for SMILES strings, trained on ~2M unique canonical SMILES from ChEMBL 36. It is the SMILES counterpart to ApeTokenizer-SELFIES, released alongside ModernMolBERT.

This model is an NF4 (Normal Float 4-bit) quantized version of the base model InstaDeepAI/nucleotide-transformer-2.5b-multi-species. The checkpoint was quantized using the BitsAndBytes library with double quantization enabled and BF16 computation.

> [!WARNING] > This is a model trained on publicly available data. While we've done our best to curate the data, the model performance can still improve. Proceed with caution.

## Important Notice If you are using GENERator for sequence generation, please ensure that the length of each input sequence is a multiple of 6. This can be achieved by either: 1. Padding the sequence on the left with 'A' (left padding); 2. Truncating the sequence from the left (left truncation).

 

 

 

 

Back to basics: Observed statistics are sufficient to predict drug responses

!IntelliFold Cover

Medical-GPT-OSS-Swallow-120B is a medical-domain language model based on tokyotech-llm/GPT-OSS-Swallow-120B-RL-v0.1. It is designed to support research and development toward safe and trustworthy AI for Japanese clinical settings.

Medical-Qwen3-Swallow-30B-A3B is a medical-domain language model based on tokyotech-llm/Qwen3-Swallow-30B-A3B-RL-v0.2. It is designed to support research and development toward safe and trustworthy AI for Japanese clinical settings.

!Pretrainloss

Mirror of the Boltz-2 structure- and affinity-prediction weights, packaged for use with tt-bio on Tenstorrent hardware. The files are byte-for-byte identical to the upstream Boltz-2 release; this repo simply hosts them on the Hugging Face Hub so tt-bio can fetch them with huggingface_hub like every…

This repository contains an MLX packaging of OpenMed/OpenMed-PII-ClinicalE5-Small-33M-v1 for Apple Silicon inference with OpenMed.