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Dans-PersonalityEngine-V1.2.0-24b ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠀⠄⠀⡂⠀⠁⡄⢀⠁⢀⣈⡄⠌⠐⠠⠤⠄⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⡄⠆⠀⢠⠀⠛⣸⣄⣶⣾⡷⡾⠘⠃⢀⠀⣴⠀⡄⠰⢆⣠⠘⠰⠀⡀⠀⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠃⠀⡋⢀⣤⡿⠟⠋⠁⠀⡠⠤⢇⠋⠀⠈⠃⢀⠀⠈⡡⠤⠀⠀⠁⢄⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠁⡂⠀⠀⣀⣔⣧⠟⠋⠀⢀⡄⠀⠪⣀⡂⢁⠛⢆⠀⠀⠀⢎⢀⠄⢡⠢⠛⠠⡀⠀⠄⠀⠀ ⠀⠀⡀⠡⢑⠌⠈⣧⣮⢾⢏⠁⠀⠀⡀⠠⠦⠈⠀⠞⠑⠁⠀⠀⢧⡄⠈⡜⠷⠒⢸⡇⠐⠇⠿⠈⣖⠂⠀ ⠀⢌⠀⠤⠀⢠⣞⣾⡗⠁⠀⠈⠁⢨⡼⠀⠀⠀⢀⠀⣀⡤⣄⠄⠈⢻⡇⠀⠐⣠⠜⠑⠁⠀⣀⡔⡿⠨⡄…

# fernandoruiz/medgemma-4b-it-Q4_0-GGUF This model was converted to GGUF format from google/medgemma-4b-it using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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

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

# Mol-Llama-3.1-8B-Instruct [Project Page] [Paper] [GitHub]

🚀 Meerkat-8B is a new instruction-tuned medical AI system of the Meerkat model family. The model was based on the Meta's Llama-3-8B-Instruct model and fine-tuned using our new synthetic dataset consisting of high-quality chain-of-thought reasoning paths sourced from 18 medical textbooks, along…

🚀 Meerkat-7B-v1.0 is an instruction-tuned medical AI system that surpasses the passing threshold of 60% for the United States Medical Licensing Examination (USMLE) for the first time among all 7B-parameter models. The model was trained using our new synthetic dataset consisting of high-quality…

This is https://huggingface.co/kingabzpro/Qwen-3-32B-Medical-Reasoning applied to https://huggingface.co/Qwen/Qwen3-32B Original model card created by @kingabzpro

GP-MoLFormer is a class of models pretrained on SMILES string representations of 0.65-1.1B molecules from ZINC and PubChem. This repository is for the model pretrained on all the unique molecules from both datasets.

Model Repo: xformai/qwen-0.6b-mentalhealth-support Base Model: Qwen/Qwen-0.5B Task: Empathetic Conversational AI for mental health & emotional support Fine-Tuned By: XformAI

### Note: This model is copied version of DNABERT-2 which removes the FlashAttention integration with Trition. This allows the model to be installed off HuggingFace without having to uninstall Triton. Running the below example code yields identical output compared to the original verison.

## Model Description EYE-Llama_gqa is a large language model specifically designed for ophthalmic question-answering (QA). It is built upon the Llama 2 architecture and fine-tuned on a the EYE-lit and EYE-QA+ dataset.

## Overview This project focuses on curating and modeling bioactivity data of small molecules targeting immune receptors. Using datasets from ImmtorLig_DB, we applied machine learning techniques to predict interactions between small molecules and immune receptors or cytokines, aiding drug discovery…

本模型基于 trueto/medbert-base-chinese 预训练模型，结合 BiLSTM 和 CRF 构建而成，用于中文医疗命名实体识别（NER）任务。

This model card describes the ClinicalBERT model, which was trained on a large multicenter dataset with a large corpus of 1.2B words of diverse diseases we constructed. We then utilized a large-scale corpus of EHRs from over 3 million patient records to fine tune the base language model.

This is the full precision (f16) GGUF version of a model trained for medical chatbot and dental implant assistant tasks. It combines general doctor–patient dialogue understanding with domain-specific Q&A derived from Straumann® dental implant system manuals.

This project fine-tunes the meta-llama/Llama-4-Scout-17B-16E-Instruct model using a medical reasoning dataset (FreedomIntelligence/medical-o1-reasoning-SFT) with 4-bit quantization for memory-efficient training.

Covering 12 Major Languages including English, Chinese, French, Hindi, Spanish, Arabic, Russian, Japanese, Korean, German, Italian, Portuguese and 38 Minor Languages So far.

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Protein solubility is a critical factor in both pharmaceutical research and production processes, as it can significantly impact the quality and function of a protein. This is an example for finetuning ibm/biomed.omics.bl.sm-ted-458m for protein solubility prediction (binary classification) based…

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This deep learning model is designed for ECG image classification, fine-tuned using ResNet-50. It can classify ECG images into different categories to assist in heart disease detection.

Diabetica: Adapting Large Language Model to Enhance Multiple Medical Tasks in Diabetes Care and Management

An SCVI model and minified AnnData of the Tahoe-100M dataset from Vevo Tx.

PPTStab: Prediction and Designing of thermostable proteins with a desired melting temperature

INDUS-Retriever-small (previously nasa-smd-ibm-st.38m) is a Bi-encoder sentence transformer model, that is fine-tuned from distilled version of nasa-smd-ibm-v0.1 encoder model. it is a smaller version of nasa-smd-ibm-st with better performance, using fewer parameters (shown below).

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

한국어 모델을 이용한 SapBERT(Self-alignment pretraining for BERT)입니다. 한·영 의료 용어 사전인 KOSTOM을 사용해 한국어 용어와 영어 용어를 정렬했습니다. 참고: SapBERT, Original Code

This is the base model of GenomeOcean-4B. It is trained with Causal Language Modeling (CLM) and uses a BPE tokenizer with 4096 tokens. It supports a maximum sequence length of 10240 tokens (~50kbp).

# GPN trained on Arabidopsis thaliana and 7 other Brassicales See https://github.com/songlab-cal/gpn for more details.

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The Clinical Assertion and Negation Classification BERT is introduced in the paper Assertion Detection in Clinical Notes: Medical Language Models to the Rescue? . The model helps structure information in clinical patient letters by classifying medical conditions mentioned in the letter into…

BiomedCLIP is a biomedical vision-language foundation model that is pretrained on PMC-15M, a dataset of 15 million figure-caption pairs extracted from biomedical research articles in PubMed Central, using contrastive learning.

Model from this repo. Model used to be in Dropbox/GDrive, leading to issues with download

# FremyCompany/BioLORD-2023 This model was trained using BioLORD, a new pre-training strategy for producing meaningful representations for clinical sentences and biomedical concepts.

# FremyCompany/BioLORD-2023-M This model was trained using BioLORD, a new pre-training strategy for producing meaningful representations for clinical sentences and biomedical concepts.

HuatuoGPT-o1-72B

HuatuoGPT-o1-7B

Using llama.cpp release b4404 for quantization.

# MMedS-Llama3 💻Github Repo 🖨️arXiv Paper

HuatuoGPT-o1-8B

Accurate prediction of drug-target binding affinity is essential in the early stages of drug discovery. This is an example of finetuning ibm/biomed.omics.bl.sm-ted-400 the task. Prediction of binding affinities using pKd, the negative logarithm of the dissociation constant, which reflects the…