WWTCyberLab/gemma-4-E2B-it-abliterated
LoRA-style vs google/gemma-4-E2B-it. Looks like a merged LoRA (or a fine-tune with frozen norms): only the weight matrices of down_proj, gate_proj, o_proj, up_proj changed, in 24 of 35 layers; norms, biases and embeddings are untouched.
Tensors changed: MLP 72/585, Norms 0/453, other 0/240, Attention 24/727, Embeddings 0/6
2 derivatives checked
- mradermacher/gemma-4-E2B-it-abliterated-GGUF: Same weights, converted (fewer layers)
- mradermacher/gemma-4-E2B-it-abliterated-i1-GGUF: Quantization (fewer layers)