clarify updated embeddings structure

README.md

@@ -69,14 +69,10 @@ dataset/
         ...
         image_set_63.tar.gz
 embeddings/
-    biocap/
-        txt_emb_species.json
-        txt_emb_species.npy
-    bioclip/
-        txt_emb_species.json
-        txt_emb_species.npy
+    txt_emb_biocap.npy
+    txt_emb_bioclip.npy
     txt_emb_species.json
-    txt_emb_species.npy
+    txt_emb_species.npy    # duplicate of txt_emb_bioclip.npy to support backwards compatibility
 metadata/
     catalog.csv
     species_level_taxonomy_chains.csv
@@ -94,7 +90,7 @@ visuals/
     phyla_ToL_tree.png
 ```
 
-[BioCLIP](https://huggingface.co/imageomics/bioclip) and [BioCAP](https://huggingface.co/imageomics/biocap) text embeddings for TreeOfLife-10M images are provided under `embeddings/<model-name>/`. The BioCLIP text embeddigns are duplicated in the `embeddings/` to maintain [`pybioclip`](http://github.com/Imageomics/pybioclip) functionality for versions 2.1.1 and earlier, which do not incorporate BioCAP as a "Tree of Life Model".
+[BioCLIP](https://huggingface.co/imageomics/bioclip) and [BioCAP](https://huggingface.co/imageomics/biocap) text embeddings for TreeOfLife-10M images are provided under `embeddings/txt_emb_<model-name>.npy`. The BioCLIP text embeddigns are duplicated as `txt_emb_species.npy` to maintain [`pybioclip`](http://github.com/Imageomics/pybioclip) functionality for versions 2.1.1 and earlier, which do not incorporate BioCAP as a "Tree of Life Model".
 
 Each `image_set` is approximately 30GB and contains 100 thousand images, each named `<treeoflife_id>.jpg`. 
 We cannot reproduce the `iNat21` data, but step-by-step [***reproduction instructions***](https://github.com/Imageomics/bioclip/blob/main/docs/imageomics/treeoflife10m.md#reproduce-treeoflife-10m) are provided on the BioCLIP GitHub repository to recreate the proper webdataset structure. This process will produce a collection of files named `shard-######.tar` in a `train`, `val`, and `train_small` folder with which to work.