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A compact protein language model distilled from ProtGPT2 using complementary-regularizer distillation---a method that combines uncertainty-aware position weighting with calibration-aware label smoothing to achieve 54% better perplexity than standard knowledge distillation at 9.4x compression.

A compact protein language model distilled from ProtGPT2 using complementary-regularizer distillation---a method that combines uncertainty-aware position weighting with calibration-aware label smoothing to achieve 87% better perplexity than standard knowledge distillation at 20x compression.

# ibm/biomed.sm.mv-te-84m-MoleculeNet-ligand_scaffold-BACE-101 biomed.sm.mv-te-84m is a multimodal biomedical foundation model for small molecules created using MMELON (Multi-view Molecular Embedding with Late Fusion), a flexible approach to aggregate multiple views (sequence, image, graph) of…

# ibm-research/biomed.sm.mv-te-84m biomed.sm.mv-te-84m is a multimodal biomedical foundation model for small molecules created using MMELON (Multi-view Molecular Embedding with Late Fusion), a flexible approach to aggregate multiple views (sequence, image, graph) of molecules in a foundation model…

## Model Description This repository contains the weights for the Borzoi model, a model designed to predict functional genomic tracks from genomic DNA sequences.

The complete neuron-to-neuron connectivity matrix extracted from a nanometer-resolution reconstruction of human temporal cortex (H01 dataset, Google/Harvard/Lichtman Lab).

ONNX export of the Cellpose cpsam (Cellpose-SAM) model for cell segmentation in microscopy images.

Model weights, configurations, and vocabularies for CpGPT: A Foundation Model for DNA Methylation.

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🌟 Github | 📥 Model Download | 📚 Dataset | 📄 Paper Link | 🌐 Project Page

From Inquiry to Decision: Building Trustworthy Medical AI

A Neural Machine Translation (NMT) model based on a custom Transformer (Encoder-Decoder) architecture, trained from scratch. This model is designed to translate English sentences into Hebrew using multilingual encoding and specialized layer configurations.

Gengram is a novel conditional memory module designed for genomic foundation models (GFMs) that introduces explicit motif memory retrieval to enhance Transformer-based DNA sequence modeling. Unlike traditional GFMs that rely on dense computation to implicitly infer multi-nucleotide motifs, Gengram…

WiNGPT 是一个基于GPT的医疗垂直领域大模型，旨在将专业的医学知识、医疗信息、数据融会贯通，为医疗行业提供智能化的医疗问答、诊断支持和医学知识等信息服务，提高诊疗效率和医疗服务质量。

Matěj Pekár, Vít Musil, Rudolf Nenutil, Petr Holub, Tomáš Brázdil

This model is a fine-tuned version of google/medgemma-1.5-4b-it specialized for mammogram analysis and breast imaging interpretation.

AVAILABLE NOW THE LATEST ITERATION OF THE ALOE FAMILY! ALOE BETA 8B AND ALOE BETA 70B VERSIONS. These include: Better overall performance More thorough alignment and safety * License compatible with more uses

Aloe: A Family of Fine-tuned Open Healthcare LLMs

While large language models (LLMs) have achieved impressive progress, their application in scientific domains such as chemistry remains hindered by shallow domain understanding and limited reasoning capabilities. In this work, we focus on the specific field of chemistry and develop a Chemical…

ChemDFM-v2.0 is the latest non-thinking model of ChemDFM, the pioneering open-sourced dialogue foundation model for Chemistry and molecule science.

Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants.

PII Detection Model | 44M Parameters | Open Source

PII Detection Model | 434M Parameters | Open Source

An efficient machine-learning interatomic potential for molecular dynamics simulations of organic and biological systems trained on an extension of the SPICE2 dataset. The model comes in two sizes (S and M).

This is a MobileViT (Small) model fine-tuned on the Processed Diabetic Retinopathy dataset.

> [!NOTE] > Inspired by the thought of: what if you could speak to an offline medical assistant that doesn't decline to answer some of your questions?

TM-Vec 2: Transformer-based architecture for remote homology detection.

The MediPhi Model Collection comprises 7 small language models of 3.8B parameters from the base model Phi-3.5-mini-instruct specialized in the medical and clinical domains. The collection is designed in a modular fashion. Five MediPhi experts are fine-tuned on various medical corpora (i.e.

The MediPhi Model Collection comprises 7 small language models of 3.8B parameters from the base model Phi-3.5-mini-instruct specialized in the medical and clinical domains. The collection is designed in a modular fashion. Five MediPhi experts are fine-tuned on various medical corpora (i.e.

The MediPhi Model Collection comprises 7 small language models of 3.8B parameters from the base model Phi-3.5-mini-instruct specialized in the medical and clinical domains. The collection is designed in a modular fashion. Five MediPhi experts are fine-tuned on various medical corpora (i.e.

The MediPhi Model Collection comprises 7 small language models of 3.8B parameters from the base model Phi-3.5-mini-instruct specialized in the medical and clinical domains. The collection is designed in a modular fashion. Five MediPhi experts are fine-tuned on various medical corpora (i.e.

The MediPhi Model Collection comprises 7 small language models of 3.8B parameters from the base model Phi-3.5-mini-instruct specialized in the medical and clinical domains. The collection is designed in a modular fashion. Five MediPhi experts are fine-tuned on various medical corpora (i.e.

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

## Description: Geneformer is a foundational transformer model pretrained on a large-scale corpus of single-cell transcriptomes to enable context-specific predictions in settings with limited data in network biology. This model version was continually pretrained on ~14 million cancer transcriptomes…

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

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

## Model Overview PlantBiMoE is a DNA language model trained on 42 representative plant species genomes. More specifically, PlantBiMoE uses the BiMamba and SparseMoE architecture with a masked language modeling objective to leverage highly available genotype data from 42 different plant speices to…

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