prithivMLmods/epsilon-ocr-d.markdown-post3.0.m
LoRA-style vs Qwen/Qwen2.5-VL-3B-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, proj, q_proj, qkv, up_proj, v_proj changed, in 36 of 36 layers; norms, biases and embeddings are untouched.
Tensors changed: Embeddings 0/2, Norms 0/138, MLP 204/304, Attention 208/380
3 derivatives checked
- mradermacher/epsilon-ocr-d.markdown-post3.0.m-i1-GGUF: Quantization (fewer layers)
- mradermacher/epsilon-ocr-d.markdown-post3.0.m-GGUF: Same weights, converted (fewer layers)
- prithivMLmods/epsilon-ocr-d.markdown-post3.0.m-GGUF: Same weights, converted (fewer layers)