Address embedding update with updated models

Nobody has claimed this yet.

BioCLIP 2.5 will be the new family of models (BioCLIP 2.5-H, BioCLIP 2.5-L, etc., where the letter references the CLIP model size).
- All these models are/will be trained on the revised TreeOfLife-200M, which includes an additional 19M images and more cleaning, the taxonomy remains un-changed.
- **Text embeddings will all be under model name folders** [here](https://huggingface.co/datasets/imageomics/TreeOfLife-200M/tree/main/embeddings).
- This is a breaking change for the pybioclip embed feature (as explained below).
- pybioclip default model will remain BioCLIP 2 because 2.5 is quite a bit larger, but it can still be used with pybioclip (we may update to 2.5-L, once that is ready).

The question for pybioclip is how we address a breaking change to the embed feature, since embeddings are a hard-coded pull from `embeddings/ txt_emb_species.npy` and `embeddings/ txt_emb_species.json` at the repo root (see [code](https://github.com/Imageomics/pybioclip/blob/main/src/bioclip/predict.py#L343)).

Related to #160

Start in src/bioclip/predict.py around line 343, where the embed feature reads embeddings/ txt_emb_species.npy and embeddings/ txt_emb_species.json. Compare those hard-coded paths with the model-name folders in the TreeOfLife-200M embeddings dataset and review the BioCLIP 2.5 model naming described here. Done means pybioclip supports the revised layout without breaking the default BioCLIP 2 behavior.

Written by the indexing model from the issue text.