40 lines
1.3 KiB
Markdown
40 lines
1.3 KiB
Markdown
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---
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license: llama3.1
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language:
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- en
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base_model:
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- meta-llama/Llama-3.1-8B-Instruct
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pipeline_tag: feature-extraction
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library_name: transformers
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tags:
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- biology
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- omics
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- bio-reasoning
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- scRNA-seq
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- PPI
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---
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# Overview
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This is the CellHermes model, based on the LLaMA-3.1-8B-instruct architecture developed by Meta,
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fine-tuned using single-cell RNA sequencing (scRNA-seq) datasets from CellxGene
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and PPI network from BioGRID. CellHermes is an innovative framework for adapting existing large language models (LLMs) to
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omics data by transforming various omics data into natural language. This transformation enables LLMs to leverage their powerful understanding and reasoning capabilities for
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various omics tasks, including perturbation prediction, cell fitness prediction, gene-disease association classification, etc.
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# Training Data
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This model was trained on over 0.2 million human transcriptome instruction data and 0.2 million PPI network datasets
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from CellxGene and BioGRID. This dataset covers a broad range of cell types and conditions
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from multiple tissues in both human.
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# Tasks
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This model is designed for:
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- Omics data understanding.
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# CellHermes Links
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- GitHub: https://github.com/theislab/CellHermes
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- Paper:
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# LLaMa-3.1-8B-Instruct Links
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- Paper: https://arxiv.org/abs/2407.21783
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- Hugging Face: https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct
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