clouditera/secgpt
LoRA-style vs Qwen/Qwen2.5-14B-Instruct. 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 48 of 48 layers; norms, biases and embeddings are untouched.
Tensors changed: Embeddings 0/1, Norms 0/97, MLP 144/144, Attention 192/336, lm_head 0/1
5 derivatives checked
- jinao/secgpt-Q4_K_M-GGUF: Not comparable yet
- mradermacher/secgpt-i1-GGUF: Quantization
- mradermacher/secgpt-GGUF: Quantization
- featherless-ai-quants/clouditera-secgpt-GGUF: Quantization
- kainatq/KingOmini_14b_v1: Full fine-tune
1 other repos hold byte-for-byte identical weight files.