EpistemeAI/OpenMedResearch-Gemma-4E4N
LoRA-style vs unsloth/gemma-4-E4B-it. Looks like a merged LoRA (or a fine-tune with frozen norms): only the weight matrices of down_proj, gate_proj, k_proj, o_proj, q_proj, up_proj, v_proj changed, in 42 of 42 layers; norms, biases and embeddings are untouched.
Tensors changed: MLP 126/606, Norms 0/502, other 0/261, Attention 168/755, Embeddings 0/6
4 derivatives checked
- mradermacher/OpenMedResearch-Gemma-E4N-GGUF: Same weights, converted (fewer layers)
- mradermacher/OpenMedResearch-Gemma-4E4N-GGUF: Same weights, converted (fewer layers)
- mradermacher/OpenMedResearch-Gemma-4E4N-i1-GGUF: Quantization (fewer layers)
- EpistemeAI/OpenMedResearch-Gemma-4E4N-8bit: Quantization (fewer layers)