Find open-source science resources
A directory of tools, AI models, datasets, and research resources for biotech, bioinformatics, and other scientific fields. Aggregated from curated GitHub awesome-lists, HuggingFace, bio.tools, Bioconductor, and more.
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477 of 7,078 resources
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From Inquiry to Decision: Building Trustworthy Medical AI
Raziel1234/OSTLM
by Raziel1234A 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.
winninghealth/WiNGPT2-Llama-3-8B-Chat
by winninghealthWiNGPT 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。
RationAI/LSP-DETR
by RationAIMatěj Pekár, Vít Musil, Rudolf Nenutil, Petr Holub, Tomáš Brázdil
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
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
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?
microsoft/MediPhi-Guidelines
by microsoftThe 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.
microsoft/MediPhi-Clinical
by microsoftThe 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.
microsoft/MediPhi-PubMed
by microsoftThe 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.
microsoft/MediPhi
by microsoftThe 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.
microsoft/MediPhi-Instruct
by microsoftThe 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.
mradermacher/Biomni-R0-32B-Preview-i1-GGUF
by mradermacherFor a convenient overview and download list, visit our model page for this model.
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ZJU-AI4H/Hulu-Med-4B
by ZJU-AI4HHulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding
Large Language and Vision Assistant for bioMedicine (i.e., “LLaVA-Med”) is a large language and vision model trained using a curriculum learning method for adapting LLaVA to the biomedical domain. It is an open-source release intended for research use only to facilitate reproducibility of the…
microsoft/llava-med-7b-delta
by microsoftThis model was added by Hugging Face staff.
!1
InstaDeepAI/BulkRNABert
by InstaDeepAIBulkRNABert is a transformer-based, encoder-only language model pre-trained on bulk RNA-seq profiles from the TCGA dataset using self-supervised masked language modeling, following the original BERT framework. The model is trained to reconstruct randomly masked gene expression values from their…
ChemFIE-BED is a sentence-transformers based on gbyuvd/chemselfies-base-bertmlm fine-tuned on around (for now) 2 million pairs of valid molecules' SELFIES (Krenn et al. 2020) taken from COCONUTDB (Sorokina et al. 2021) and ChemBL34 (Zdrazil et al. 2023).
vandijklab/C2S-Scale-Gemma-2-27B
by vandijklabGitHub homepage: Cell2Sentence GitHub
This model is a fine-tuned version of google/medgemma-4b-it adapted for binary mammogram classification on the OMAMA 256×256 dataset. The dataset consists of ~154k mammogram image slices (.npz) with metadata JSONs providing labels (NonCancer, Cancer).
mradermacher/Gemma-2-2B-MedicalQA-Assistant-GGUF
by mradermacherFor a convenient overview and download list, visit our model page for this model.
The Nucleotide Transformers are a collection of foundational language models that were pre-trained on DNA sequences from whole-genomes. Compared to other approaches, our models do not only integrate information from single reference genomes, but leverage DNA sequences from over 3,200 diverse human…
DermLIP is a vision-language model for dermatology, trained on the Derm1M dataset—the largest dermatological image-text corpus to date. This model variant (PanDerm-base-w-PubMed-256) utilizes domain-specific pretraining to deliver superior performance compared to other DermLIP variants..
stanfordmimi/MedVAL-4B
by stanfordmimiMedVAL-4B (medical text validator) is a language model fine-tuned to assess AI-generated medical text outputs at near physician-level reliability.
This model is a lightweight model pre-trained on SELFIES (Self-Referencing Embedded Strings) representations of molecules. It is trained on 2.7M unique and valid molecules taken from COCONUTDB and ChemBL34, with 7.3M total generated masked examples.
nvidia/AMPLIFY_350M
by nvidia> [!NOTE] > This model has been optimized using NVIDIA's TransformerEngine > library. Slight numerical differences may be observed between the original model and the optimized > model. For instructions on how to install TransformerEngine, please refer to the > official documentation.
nvidia/AMPLIFY_120M
by nvidia> [!NOTE] > This model has been optimized using NVIDIA's TransformerEngine > library. Slight numerical differences may be observed between the original model and the optimized > model. For instructions on how to install TransformerEngine, please refer to the > official documentation.
Here is the pretrained version of PolyTAO, the first pretrained generative language model for polymer design.
lingshu-medical-mllm/Lingshu-32B
by lingshu-medical-mllmWebsite 🤖 7B Model 🤖 32B Model MedEvalKit Technical Report Lingshu MCP
lingshu-medical-mllm/Lingshu-7B
by lingshu-medical-mllmWebsite 🤖 7B Model 🤖 32B Model MedEvalKit Technical Report Lingshu MCP
The Nucleotide Transformers are a collection of foundational language models that were pre-trained on DNA sequences from whole-genomes. Compared to other approaches, our models do not only integrate information from single reference genomes, but leverage DNA sequences from over 3,200 diverse human…
The Nucleotide Transformers are a collection of foundational language models that were pre-trained on DNA sequences from whole-genomes. Compared to other approaches, our models do not only integrate information from single reference genomes, but leverage DNA sequences from over 3,200 diverse human…
stanfordmimi/RoentGen-v2
by stanfordmimiPalmyra-Med, a powerful LLM designed for healthcare