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This model is a BERT-like sequence classifier for 221 human protein drug targets, fine-tuned from gbyuvd/chemselfies-base-bertmlm on a dataset derived ChemBL34 (Zdrazil et al. 2023). It predicts potential drug targets using chemical structures represented as SELFIES (Self-Referencing Embedded…

The Mistral-DNA-v1-138M-bacteria Large Language Model (LLM) is a pretrained generative DNA text model with 17.31M parameters x 8 experts = 138.5M parameters. It is derived from Mistral-7B-v0.1 model, which was simplified for DNA: the number of layers and the hidden size were reduced.

Model Card for "medllama" ---------------------------

This is a ReactionT5 pre-trained to predict the products of reactions.

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## Model Overview AgroNT is a DNA language model trained on primarily edible plant genomes. More specifically, AgroNT uses the transformer architecture with self-attention and a masked language modeling objective to leverage highly available genotype data from 48 different plant speices to learn…

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.

# Medical-Llama3-v2 Fine-Tuned Llama3 for Medical Q&A This repository provides a fine-tuned version of the powerful Llama3 8B model, specifically designed to answer medical questions in an informative way. It leverages the rich knowledge contained in the AI Medical Chatbot dataset…

This is an official model checkpoint for Asclepius-Mistral-7B-v0.3 (arxiv). This model is an enhanced version of Asclepius-7B, by replacing the base model with Mistral-7B-v0.3 and increasing the max sequence length to 8192.

This is an official model checkpoint for Asclepius-Llama3-8B (arxiv). This model is an enhanced version of Asclepius-7B, by replacing the base model with Llama-3 and increasing the max sequence length to 8192.

The Me-LLaMA model consists of two foundation models: Me-LLaMA 13B and Me-LLaMA 70B, along with their chat-enhanced counterparts, Me-LLaMA 13B-chat and Me-LLaMA 70B-chat. These models are designed for superior chat and instruction-following capabilities.

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.

This model is developed by Basel Anaya.

# MMedLM 💻Github Repo 🖨️arXiv Paper

This model is deprecated. please use the updated sentence transformer model here: https://huggingface.co/nasa-impact/nasa-smd-ibm-st-v2. Alternatively, you can also use distilled version of the model here: https://huggingface.co/nasa-impact/nasa-ibm-st.38m

# JSL-MedLlama-3-8B-v2.0

Reference: R. Luu and M.J. Buehler, "BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-Inspired Materials," Adv. Science, 2023, DOI: https://doi.org/10.1002/advs.202306724

Medical mT5: An Open-Source Multilingual Text-to-Text LLM for the Medical Domain

# ChemLLM-7B-Chat-1.5-DPO: LLM for Chemistry and Molecule Science ChemLLM-7B-Chat-1.5-DPO, The First Open-source Large Language Model for Chemistry and Molecule Science, Build based on InternLM-2 with ❤

EndoViT

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This model is a fine-tuned version of DeBERTa on the PubMED Dataset.

Using llama.cpp release b2440 for quantization.

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## 💡 Model description This repo contains a large molecular generative model built with molecular language SELFIES.

Using llama.cpp commit fa97464 for quantization.

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# Mr-Grammatology-clinical-problems-Mistral-7B-0.5 !image/png

Abstract:

This is a merge of pre-trained language models created using mergekit.

Abstract:

This is a merge of pre-trained language models created using mergekit.

This is a merge of pre-trained language models created using mergekit.

SMILES2IUPAC-canonical-base was designed to accurately translate SMILES chemical names to IUPAC standards.

# TinyLlama-1.1B

The T5 Large for Medical Text Summarization is a specialized variant of the T5 transformer model, fine-tuned for the task of summarizing medical text. This model is designed to generate concise and coherent summaries of medical documents, research papers, clinical notes, and other…

This is official model checkpoint for Asclepius-13B (arxiv). This model is the first publicly shareable clinical LLM, trained with synthetic data.

Google ViT model is finetuned on lung and colon histopathology image classification dataset. The dataset is available on Kaggle.

Details coming soon

# Meditron 70B - GGUF - Model creator: EPFL LLM Team - Original model: Meditron 70B

A Vision Transformer (ViT) image classification model. \ Trained on 15M histology patches from PAIP and TCGA. \ Used the MoCo v3 self supervised learning method.

This is Vision Transformer model trained for cancer classification. To make single model to predict any cancer, I trained this ViT model. following are the cancer types that model can predict: Brain cancer Breast Cancer (histopathology) Lung & Colon Cancer (histopathology) Cervical Caner Kidney…

This model was finetuned on concatenated pairs of interacting proteins in much the same way as PepMLM. It is meant to generate interaction partners for proteins using the masked language modeling capabilities of ESM-2. The model is not well tested, so use with caution.

ProstT5 is a protein language model (pLM) which can translate between protein sequence and structure. !ProstT5 pre-training and inference

A Vision Transformer (ViT) image classification model. \ Trained by Owkin on 40 million pan-cancer histology tiles from TCGA-COAD.

A Vision Transformer (ViT) image classification model. \ Trained by Owkin on 40M pan-cancer histology tiles from TCGA. \ Fine-tuned on LC25000's lung subset.

## Model Description The "Bird Species Classifier" is a state-of-the-art image classification model designed to identify various bird species from images. It uses the EfficientNet architecture and has been fine-tuned to achieve high accuracy in recognizing a wide range of bird species.