Merge branch 'main' of https://huggingface.co/datasets/AstroCompress/SBI-16-2D into main

README.md

@@ -21,50 +21,54 @@ pip install datasets astropy
 
 There are two datasets: `tiny` and `full`, each with `train` and `test` splits. The `tiny` dataset has 2 2D images in the `train` and 1 in the `test`. The `full` dataset contains all the images in the `data/` directory.
 
-## Use from Huggingface Directly
+## Local Use (RECOMMENDED)
 
-To directly use from this data from Huggingface, you'll want to log in on the command line before starting python:
+Alternatively, you can clone this repo and use directly without connecting to hf:
 
 ```bash
-huggingface-cli login
+git clone https://huggingface.co/datasets/AstroCompress/SBI-16-2D
 ```
 
-or
-
+To pull all data files:
 ```
-import huggingface_hub
-huggingface_hub.login(token=token)
+git lfs pull
 ```
 
-Then in your python script:
+Then `cd SBI-16-3D` and start python like:
 
 ```python
 from datasets import load_dataset
-dataset = load_dataset("AstroCompress/SBI-16-2D", "tiny")
+dataset = load_dataset("./SBI-16-2D.py", "tiny", data_dir="./data/")
 ds = dataset.with_format("np")
 ```
 
-## Local Use
-
-Alternatively, you can clone this repo and use directly without connecting to hf:
+Now you should be able to use the `ds` variable like:
 
-```bash
-git clone https://huggingface.co/datasets/AstroCompress/SBI-16-2D
+```python
+ds["test"][0]["image"].shape # -> (TBD)
 ```
 
-Then `cd SBI-16-3D` and start python like:
+Note of course that it will take a long time to download and convert the images in the local cache for the `full` dataset. Afterward, the usage should be quick as the files are memory-mapped from disk.
 
-```python
-from datasets import load_dataset
-dataset = load_dataset("./SBI_16_2D.py", "tiny", data_dir="./data/")
-ds = dataset.with_format("np")
+## Use from Huggingface Directly
+
+To directly use from this data from Huggingface, you'll want to log in on the command line before starting python:
+
+```bash
+huggingface-cli login
 ```
 
-Now you should be able to use the `ds` variable like:
+or
 
-```python
-ds["test"][0]["image"].shape # -> (TBD)
+```
+import huggingface_hub
+huggingface_hub.login(token=token)
 ```
 
-Note of course that it will take a long time to download and convert the images in the local cache for the `full` dataset. Afterward, the usage should be quick as the files are memory-mapped from disk.
+Then in your python script:
 
+```python
+from datasets import load_dataset
+dataset = load_dataset("AstroCompress/SBI-16-2D", "tiny")
+ds = dataset.with_format("np")
+```