Vikhrmodels/Vikhr-Llama-3.2-1B-Instruct
LoRA-style vs meta-llama/Llama-3.2-1B-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 16 of 16 layers; norms, biases and embeddings are untouched.
Tensors changed: Embeddings 0/1, Norms 0/33, MLP 48/48, Attention 64/64
6 derivatives checked
- Vikhrmodels/Vikhr-Llama-3.2-1B-instruct-GGUF: Same weights, converted
- tinyopsec/Vikhr-Llama-3.2-1B-Instruct-GGUF: Same weights, converted
- mradermacher/Vikhr-Llama-3.2-1B-Instruct-GGUF: Same weights, converted
- featherless-ai-quants/Vikhrmodels-Vikhr-Llama-3.2-1B-Instruct-GGUF: Quantization
- tensorblock/Vikhr-Llama-3.2-1B-Instruct-GGUF: Quantization
- Vikhrmodels/Vikhr-Llama-3.2-1B-Instruct-abliterated: Full fine-tune
2 other repos hold byte-for-byte identical weight files.