Nucleotide
nucleotide_transformer_downstream_tasks
Dataset Card for Dataset Name
The nucleotide_transformer_downstream_tasks dataset features the 18 downstream tasks presented in the Nucleotide Transformer paper. They consist of both binary and multi-class classification tasks that aim at providing a consistent genomics benchmark.
⚠️We note that we have revised and improved our benchmark during the peer-review process. The datasets featured in this repository are used up to this release. We highly encourage to move to the new… See the full description on the dataset page: https://huggingface.co/datasets/InstaDeepAI/nucleotide_transformer_downstream_tasks.nucleotide_transformer_downstream_tasks_revised
Dataset Card for Dataset Name
The nucleotide_transformer_downstream_tasks dataset features the 18 downstream tasks presented in the Nucleotide Transformer paper. They consist of both binary and multi-class classification tasks that aim at providing a consistent genomics benchmark.
We note that this is an updated version of this benchmark after the paper has been through peer-review. We highly encourage to move to this version in detriment of the older version.Keypoints about the… See the full description on the dataset page: https://huggingface.co/datasets/InstaDeepAI/nucleotide_transformer_downstream_tasks_revised.cross-species-single-nucleotide-annotation
Dataset Overview
The dataset consists of five tasks for cross-species modeling plant genomes at single-nucleotide resolution in plants. These tasks are:
Translation Initiation Site (TIS) Prediction
Translation Termination Site (TTS) Prediction
Splice Donor Site Prediction
Splice Acceptor Site Prediction
Evolutionary Conservation Prediction
Tasks 1-4: Site Predictions
Training Dataset: Generated from Arabidopsis chromosomes 1-4
Validation Dataset: Generated from… See the full description on the dataset page: https://huggingface.co/datasets/kuleshov-group/cross-species-single-nucleotide-annotation.omnimind-nucleotide-transformer-v2-patch
OmniMind Nucleotide Transformer v2 50m Multi-Species Patch
Repositório de modelo compatível com transformers >= 4.50 e ambiente Kaggle.
Origem
Base: InstaDeepAI/nucleotide-transformer-v2-50m-multi-species
Arquivos de peso (model.safetensors) são idênticos ao original.
modeling_esm.py e esm_config.py são a versão do cache local que carrega corretamente com transformers 4.57.4.
Modificações
modeling_esm.py: adicionado fallback local para… See the full description on the dataset page: https://huggingface.co/datasets/fabricioslv/omnimind-nucleotide-transformer-v2-patch.TATA-NOTATA-FineMistral-nucleotide_transformer_downstream_tasksDataset for Fine-tuning Mistral Model on Tata and No Tata Sequences
Description
This dataset is specifically curated for training the Mistral model to distinguish between 'tata' and 'no tata' sequences. It is derived and reformatted from a dataset originally created by InstaDeep, tailored to enhance the performance of natural language processing models in identifying specific patterns.
Dataset Information
Features: This dataset consists of sequences represented as strings under the… See the full description on the dataset page: https://huggingface.co/datasets/Kamka-IT/TATA-NOTATA-FineMistral-nucleotide_transformer_downstream_tasks.NucleotideTransformer_interpretation