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README.md

@@ -7,17 +7,19 @@ tags:
 - biology
 - genomics
 datasets:
-- Genentech/human-atac-catlas-data
+- Genentech/human-chromhmm-fullstack-data
+base_model:
+- Genentech/enformer-model
 ---
 
-# human-atac-catlas-model
+# human-chromhmm-fullstack-model
 
 ## Model Description
-This model is a multi-task binary classifier trained to predict chromatin accessibility across 204 cell types. It was trained by fine-tuning the Enformer model using the `grelu` library on top of the CATlas human enhancer dataset.
+This model is a multi-class classifier trained to classify genomic DNA sequences into one of 16 classes. It was trained by fine-tuning the Enformer model using the `grelu` library on top of the human ChromHMM fullstack annotation dataset.
 
 - **Architecture:** Fine-tuned Enformer
 - **Input:** Genomic sequences (hg38)
-- **Output:** Binary accessibility predictions for 204 cell type tasks.
+- **Output:** Probability across 16 class labels.
 
 ## Repository Content
 1. `model.ckpt`: The trained model weights and hyperparameters (PyTorch Lightning checkpoint).
@@ -32,7 +34,7 @@ from grelu.lightning import LightningModel
 from huggingface_hub import hf_hub_download
 
 ckpt_path = hf_hub_download(
-    repo_id="Genentech/human-atac-catlas-model", 
+    repo_id="Genentech/human-chromhmm-fullstack-model", 
     filename="model.ckpt"
 )