instructions for using with github

README.md

@@ -29,35 +29,11 @@ The dataset contains **32 swarms** organized into four main categories:
 
 ## Usage
 
-### Primary Use Case: Direct CSV Loading with Olmix
+### Primary Use Case: Proposing a Mix using OlmixBase
 
-The primary way to use these datasets is to load the CSV files directly and pass them to Olmix functions. This is the recommended workflow for data mixture optimization.
+The primary way to use these datasets is to download these CSVs (`ratios.csv`, `metrics.csv` together) directly and use them with the [Olmix GitHub](https://github.com/allenai/olmix) ([example](https://github.com/allenai/olmix/blob/main/configs/fits/dclm_baseline.yaml)). This is the recommended workflow for data mixture optimization.
 
 
-### Loading Metadata
-
-Each dataset includes a `meta.json` file with descriptions and details:
-
-```python
-import json
-
-with open("dclm_swarm/meta.json") as f:
-    meta = json.load(f)
-
-print(f"Description: {meta['description']}")
-print(f"Notes: {meta['notes']}")
-```
-
-### Browsing Available Datasets
-
-```bash
-# List all available swarms
-find . -name "meta.json" -exec dirname {} \;
-
-# View a specific swarm's metadata
-cat dclm_swarm/meta.json
-```
-
 ### Alternative: HuggingFace Datasets Library
 
 You can also load all swarms at once using the HuggingFace datasets library (useful for exploration):