Post
3698
Layer-wise and Pruned versions of Qwen/Qwen3-30B-A3B
* Tesor-wise: eaddario/Qwen3-30B-A3B-GGUF
* Pruned: eaddario/Qwen3-30B-A3B-pruned-GGUF
Even though the Perplexity scores of the pruned version are 3 times higher, the ARC, HellaSwag, MMLU, Truthful QA and WinoGrande scores are holding remarkably well, considering two layers were removed (5 and 39). This seems to support Xin Men et al conclusions in
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect (2403.03853)
Results summary in the model's card and test results in the ./scores directory. Questions/feedback is always welcomed.
* Tesor-wise: eaddario/Qwen3-30B-A3B-GGUF
* Pruned: eaddario/Qwen3-30B-A3B-pruned-GGUF
Even though the Perplexity scores of the pruned version are 3 times higher, the ARC, HellaSwag, MMLU, Truthful QA and WinoGrande scores are holding remarkably well, considering two layers were removed (5 and 39). This seems to support Xin Men et al conclusions in
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect (2403.03853)
Results summary in the model's card and test results in the ./scores directory. Questions/feedback is always welcomed.