prithivMLmods/GWQ2b
LoRA-style vs google/gemma-2-2b-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 26 of 26 layers; norms, biases and embeddings are untouched.
Tensors changed: Embeddings 0/1, Norms 0/105, MLP 78/78, Attention 104/104
5 derivatives checked
- mradermacher/GWQ2b-i1-GGUF: Quantization
- mradermacher/GWQ2b-GGUF: Same weights, converted
- featherless-ai-quants/prithivMLmods-GWQ2b-GGUF: Quantization
- DevQuasar-2/prithivMLmods.GWQ2b-GGUF: Same weights, converted
- Sakalti/SJT-2B-V1.1: Full fine-tune