VirtualCell2025/SE600M-embedding
Instruction from Wanwan Feng Step 1 — Generate Embeddings for All Input Files This step shows the creation of this SE600M-embedding dataset from the existing training dataset provided by the Arc Institute for the Virtual Cell Challenge. import os os.environ['MPLBACKEND'] = 'Agg' # 1. Files to process FILENAMES_TO_PROCESS = [ "competition_train.h5", "jurkat.h5", "k562.h5", "k562_gwps.h5", "rpe1.h5"… See the full description on the dataset page: https://huggingface.co/datasets/VirtualCell2025/SE600M-embedding.
| Author / organization | VirtualCell2025 |
|---|---|
| Downloads | 203 (as reported by Hugging Face) |
| Likes | 1 |
| Created | 12 August 2025 |
| Last updated at source | 17 August 2025 |
Recent changes
- 16 Oct 2026 Description: Instruction from Wanwan Feng Step 1 — Generate Embeddings for All Input Files This step shows the creation of this SE600M-embedding dataset from the existing training dataset provided by the Arc Institute for the Virtual Cell Challenge. imp → Instruction from Wanwan Feng Step 1 — Generate Embeddings for All Input Files This step shows the creation of this SE600M-embedding dataset from the existing training dataset provided by the Arc Institute for the Virtual Cell Challenge. imp
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