Config.json using illegal math, Echolabz will help you fix it..
Sorry, Everyone just wanted to let you know this model uses illegal math in the config.json. I’m not saying that to start problems, I’m saying it because I actually sat down, ran the numbers, and the math doesn’t line up with the architecture at all.
Here’s what’s going on:
The config says the model is running 32 attention heads at head_dim 128, but the hidden_size is 5376. If you run the math yourself:
128 x 32 = 4096
That is not 5376.
The only head size that actually matches 5376 is 168, not 128.
And that isn’t a guess. The config literally exposes it:
query_pre_attn_scalar = 168
That number only makes sense if the real head_dim was supposed to be 168 the whole time. So right now the model is sitting on two different head dimensions at once. That’s not allowed in attention math, and it breaks the geometry of the Q/K/V projections.
Now, here’s the part everyone is probably wondering:
“Does this affect me using the model?”
For most people, no. Regular users loading the model for inference don’t need to worry. Transformers will reshape everything internally and force the mismatch to fit. You can download it, run it, chat with it, benchmark it, whatever, and it works.
Where this becomes a real problem is if you:
merge models
train models
use LoRAs
try to export adapters
do weight surgery
use Hydra-style extraction or EchoLabz extraction methods (coming soon)
work with long-context attention
do any form of fine-tuning or token surgery
If you’re doing any of that, the illegal math will break your runs or degrade the model without warning.
If you’re not doing any of that and you’re just running the model normally, you probably won’t ever notice this issue. But the architecture is still wrong, and it should be fixed.
White paper will be out at the end of the week explaining everything in detail. Letting everyone know now so nobody wastes time on merges or adapters while the geometry is off. dont worry i have attached a Fix for you guys here
GEMMA 3 FIXED CONFIG Shadow/Echo_Raine — EchoLabZ
Replace the config.json in Gemma 3 with (config.json) with this:
"text_config": {
"hidden_size": 5376,
"head_dim": 168,
"num_attention_heads": 32,
"num_key_value_heads": 16,
"intermediate_size": 21504,
"num_hidden_layers": 62,
"query_pre_attn_scalar": 168,
"rope_scaling": {
"factor": 8.0,
"rope_type": "linear"
},
"sliding_window": 1024
}
This corrects the illegal math:
- 5376 / 32 = 168 (true head_dim)
- Removes the conflicting 128 head_dim
- Makes the model safe for merges, adapters, tuning, and extraction.