Update README.md (Again)

README.md

@@ -61,7 +61,7 @@ prototyping and planning that enables much higher sequences with less vram to as
 
 # I've decided to name this model
 
-* This model is dubbed SD15 Flow-Matching Sol - twin sister to the alternative Try2 who is named SD15 - Lune.
+* This model is dubbed SD1.5 Flow-Matching Sol - twin sister to the alternative Try2 who is named SD1.5 - Lune.
 
 Sun and Moon.
 
@@ -71,14 +71,14 @@ Sun and Moon.
 
 ![image](https://cdn-uploads.huggingface.co/production/uploads/630cf55b15433862cfc9556f/tTXp4HIQ1eIuuBf-N6lkH.png)
 
-I'm sticking to the positive spectrum here, knowing that 6 million samples isn't enough to converge sd15.
+I'm sticking to the positive spectrum here, knowing that 6 million samples isn't enough to converge SD1.5.
 I believe it will take around 10 mil to start SEEING correct shapes showing with texture other than flat or blob, but I've been wrong before - and we will make happy little bushes out of this if I am.
 
 Our flow match troopers are trying their best, but the outlooks aren't looking particularly good yet. Blobs all the way to epoch 30.
 That's roughly 200,000 samples * 30, which should be about 6 million images worth. Not enough to fully saturate the system, but more than what I used for sdxl vpred conversions.
 There may need to be a refined process with synthetic dreambooth-styled images devoted to top prio, mid prio, and low prio classes.
 
-When the distillation concludes, there will be additional finetuning after with direct images generated from sd15 using class-based specifics in any case.
+When the distillation concludes, there will be additional finetuning after with direct images generated from SD1.5 using class-based specifics in any case.
 So, it'll be an interesting outcome for both the baseline starter and the v2 trained version. 
 I have high hopes either way and I will have the class-based dreambooth-style selector ready to immediately begin after epoch 50.
 
@@ -133,7 +133,7 @@ Individual block losses have been correctly reintroduced and will train the time
 
 
 
-# Most original checkpoints are default sd15 after testing
+# Most original checkpoints are default SD1.5 after testing
 For those who downloaded the models that either exhibit blobs or don't use flow matching noise - my sincerest apologies. They are defective. Blobs are expected, standard noise is not.
 
 The CURRENT e8 has no clip or vae, so it's just sitting there standalone. This is the currently newest valid one and it functions as expected - by making blobs due to early pretraining.
@@ -151,11 +151,11 @@ If not, I'll just train it directly using a different technique without David.
 My sincerest apologies for all of the blunders and the problems. I didn't expect so many problems but I did expect some. 
 
 I ended up having to use debug to salvage epoch 8 so I wouldn't have to restart. The metrics appear corrupted as well.
-The safetensor outputs were saving the original sd15 with silently mismatched keys thanks to the diffusers script not operating as intended. Additionally, the subsystems that I implemented never tripped the flags they needed to - in order to ensure backup. So the system was culling the PTs.
+The safetensor outputs were saving the original SD1.5 with silently mismatched keys thanks to the diffusers script not operating as intended. Additionally, the subsystems that I implemented never tripped the flags they needed to - in order to ensure backup. So the system was culling the PTs.
 Between a rock and a hard place I figured out how to salvage it and here we are - thanks to a combination of Gemini's information and Claude's code debugging and problem solving the training can continue.
 
 # More faults more problems still managed to salvage the real one
-How absurd and difficult anything SD15 has been to debug.
+How absurd and difficult anything SD1.5 has been to debug.
 
 Okay I am correctly converting the valuation and can now properly test the unet for diffusion testing.