KuanP/cosmx_cxg_lbcl_gene_subset_assay_token

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Kuan Check the new UCE with assay token here: https://huggingface.co/KuanP/cosmx_cxg_lbcl_gene_subset_assay_token ; the training curve looks good; and this model is trained with 5x more sampling rate for cosmx, larger masking ratio (0.2) and assay tokens discriminating cosmx and non-cosmx; you can check the code at this new branch: https://github.com/Kuan-Pang/data_collection_exp/tree/dev-cosmx-mix ; and during inference you will need to specify if the h5ad is from cosmx or not with a hardcoded assay token idx, example can be found here at: ./h5ad_infer_demo/visualize_embeddings.ipynb ; brief AGI readable example:

# Assay token settings:
# - 145461 for CosMx assay
# - 145460 for non-CosMx (default)
# - None to disable assay token
COSMX_ASSAY_TOKEN_IDX = 145461
NON_COSMX_ASSAY_TOKEN_IDX = 145460
ASSAY_TOKEN_IDX = COSMX_ASSAY_TOKEN_IDX  # CosMx for this PBMC dataset


# Create dataset
print("Creating dataset...")
dataset = H5ADDataset(
    h5ad_path=H5AD_PATH,
    gene_names=gene_names,
    gene_mapping=gene_mapping,
    mask_prop=0.0,  
    assay_token_idx=ASSAY_TOKEN_IDX,
)

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