Update README.md

README.md

@@ -40,8 +40,8 @@ This model is still in its infancy and it's meant to be constantly updated and t
   - #### Stable:
     - No stable version available right now.
   - #### Beta:
-    - [vae.1663000.pt](https://huggingface.co/Sygil/Sygil-Muse/blob/main/vae.2200000.pt): Trained from scratch for 1.66M steps
-    - [maskgit.505000.p](https://huggingface.co/Sygil/Sygil-Muse/blob/main/maskgit.1206000.pt): Maskgit trained from the VAE for 1.20M steps
+    - [vae.2410000.pt](https://huggingface.co/Sygil/Sygil-Muse/blob/main/vae.2410000.pt): Trained from scratch for 2.41M steps
+    - [maskgit.1206000.p](https://huggingface.co/Sygil/Sygil-Muse/blob/main/maskgit.1206000.pt): Maskgit trained from the VAE for 1.20M steps
   
   Note: Checkpoints under the Beta section are updated daily or at least 3-4 times a week. This is usually the equivalent of 1-2 training session,
   this is done until they are stable enough to be moved into a proper release, usually every 1 or 2 weeks.
@@ -55,7 +55,7 @@ The model was trained on the following dataset:
 - [Imaginary Network Expanded Dataset](https://github.com/Sygil-Dev/INE-dataset) dataset.
 
 **Hardware and others**
-- **Hardware:** 1 x Nvidia RTX 3050 8GB GPU
+- **Hardware:** 1 x Nvidia RTX 3090 GPU
 - **Hours Trained:** NaN.
 - **Gradient Accumulations**: 1
 - **Batch:** 1
@@ -64,6 +64,6 @@ The model was trained on the following dataset:
 - **Resolution/Image Size**: First trained at a resolution of 64x64 and then increased to 512x512. Check the notes down below for more details on this.
 - **Dimension:** 256
 - **vq_codebook_size:** 256
-- **Total Training Steps:** 2,200,000
+- **Total Training Steps:** 2,410,000
 
-  Note: On Muse we can change the image_size or resolution at any time without having to train the model from scratch again, this allow us to first train the model at low resolution using the same `dim` and `vq_codebook_size` to train faster and then we can increase the `image_size` and use a higher resolution once the model has trained enough.
+  Note: On Muse we can change the image_size or resolution at any time without having to train the model from scratch again, this allows us to first train the model at low resolution using the same `dim` and `vq_codebook_size` to train faster and then we can increase the `image_size` and use a higher resolution once the model has trained enough.