Update README.md

README.md

@@ -26,15 +26,42 @@ Each document exists as a collection of a pdf, a tiff image with the same conten
 </center>
 
 
-### Usage
-This instance of IDL is in [webdataset](https://github.com/webdataset/webdataset) .tar format and can be used with derived forms of the webdataset library. For dataloading, the `datasets` library can readily be used, and we also recommend to use it with the chug library, an optimized library for distributed data loading.
+This instance of IDL is in [webdataset](https://github.com/webdataset/webdataset/commits/main) .tar format.
+
+### Usage with `chug`
+Check out [chug](https://github.com/huggingface/chug), our optimized library for sharded dataset loading! 
+
+```python
+import chug
+task_cfg = chug.DataTaskDocReadCfg(page_sampling='all')
+data_cfg = chug.DataCfg(
+    source='pixparse/IDL-wds',
+    split='train',
+    batch_size=None,
+    format='hfids',
+    num_workers=0,    
+)
+data_loader = chug.create_loader(
+    data_cfg,
+    task_cfg,
+)
+sample = next(iter(data_loader))
+```
+
+
+
+### Usage with datasets
+
+This dataset can also be used with webdataset library or current releases of Hugging Face `datasets`.
+Here is an example using the "streaming" parameter. We do recommend downloading the dataset to save bandwidth. 
+
 ```python
-from datasets import load_dataset
 dataset = load_dataset('pixparse/IDL-wds', streaming=True)
 print(next(iter(dataset['train'])).keys())
 >> dict_keys(['__key__', '__url__', 'json', 'ocr', 'pdf', 'tif'])
 ```
 
+
 For faster download, you can directly use the `huggingface_hub` library. Make sure `hf_transfer` is installed prior to downloading and mind that you have enough space locally. 
 
 ```python
@@ -50,38 +77,6 @@ For faster download, you can directly use the `huggingface_hub` library. Make su
  
 ```
 
-
-
-# TODO The following example uses fitz which is AGPL. We should also recommend the same with pypdf.
-
-```python
-from chug import create_wds_loader, create_doc_anno_pipe
-
-# TODO import image transforms and text transforms from pixparse.data
-
-
-decoder = create_decoder_pipe(
-    image_preprocess=image_preprocess, # callable of transforms to image tensors
-    anno_preprocess=anno_preprocess, # callable of transforms to text into tensors of labels and targets
-    image_key="pdf",
-    image_fmt="RGB",
-)
-
-loader = create_wds_loader(
-    "/my_data/idl-train-*.tar",
-    decoder,
-    is_train=True,
-    resampled=False,
-    start_interval=0,
-    num_samples=2159432,
-    workers=8,
-    batch_size=32, # adjust to your architecture capacity
-    seed=seed, # set a seed
-    world_size=world_size, # get world_size from your training environment
-)
-
-```
-
 Further, a metadata file `_pdfa-english-train-info-minimal.json` contains the list of samples per shard, with same basename and `.json` or `.pdf` extension, 
 as well as the count of files per shard. 
 
@@ -152,28 +147,7 @@ That way, columnar documents can be better separated. This is a basic heuristic
 
 For each pdf document, we store statistics on number of pages per shard, number of valid samples per shard. A valid sample is a sample that can be encoded then decoded, which we did for each sample.
 
-This instance of IDL is in [webdataset](https://github.com/webdataset/webdataset/commits/main) .tar format. It can be used with webdataset library or current releases of Hugging Face `datasets`.
-Here is an example using the "streaming" parameter. We do recommend downloading the dataset to save bandwidth. 
-
-```python
-dataset = load_dataset('pixparse/IDL-wds', streaming=True)
-print(next(iter(dataset['train'])).keys())
->> dict_keys(['__key__', '__url__', 'json', 'ocr', 'pdf', 'tif'])
-```
-
-For faster download, you can use directly the `huggingface_hub` library. Make sure `hf_transfer` is install prior to downloading and mind that you have enough space locally. 
 
-```python
- import os
- 
- os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
- 
- from huggingface_hub import HfApi, logging
- 
- #logging.set_verbosity_debug()
- hf = HfApi()
- hf.snapshot_download("pixparse/pdfa-english-train", repo_type="dataset", local_dir_use_symlinks=False)                               
-```
 ### Data, metadata and statistics.
 <center>
     <img src="https://huggingface.co/datasets/pixparse/IDL-wds/resolve/main/doc_images/idl_page_example.png" alt="An addendum from an internal legal document" width="600" height="300">