Update README.md

README.md

@@ -119,12 +119,11 @@ This repo contains the following configurations under `./models/`:
       * `descript-audio-codec` can be revisited as an RVQ-based codec since they're easier to train a model around over an FSQ codec
       * an EnCodec variant can also be revisited, as it's rather quick to get a model to have speech emerge
   * Notes can be found in the [implementation documentation](https://github.com/e-c-k-e-r/vall-e/blob/master/docs/models_v2.md).
+  * A proof-of-concept LoRA is provided.
 
 Some additional configurations have been explored with, but experiments have not been fruitful:
 * Exotic wrappers like `BitNet` seemed to yield little gains in inferencing, somehow. The memory savings is pretty much unneccessary as the models are already manageable at ~200M parameters.
 * Mamba / Mamba2-based models have shown that it's ***really*** hard to have an AR+NAR model. I really do not want to bother throwing the compute at another ~~meme~~ arch I can't easily make use of all the other tech to throw at.
-* a model using [Descript-Audio-Codec](https://github.com/descriptinc/descript-audio-codec/):
-  + the new implementation should be able to handle it.
 * a model with a causal size >1 (sampling more than one token for the AR):
   * this seems a bit unneccessary as the NAR-len modality addresses the downsides of the AR+NAR modality.
 
@@ -138,3 +137,5 @@ The only caveat is that my original dataset *does* contain (most of) these sampl
 * However, the base model already has *almost adequate* output from these speakers, but not enough to be satisfactory.
 
 LoRAs under `ckpt[ar+nar-old-llama-8]` are LoRAs married to an older checkpoint, while `ckpt` *should* work under the reference model. 
+
+LoRAs under `ckpt[nemo-larger-44khz-llama-8]` are LoRAs married to the `nemo-larger-44khz-llama-8` model.