models
Open weights, fine-tunes and adapters. Every listing here comes live from the Hugging Face Hub, attributed to it, and links back to the source.
LongCat-Flash-Lite-Sparse-Uncensored-Heretic-Native-MTP-And-LSA-Preserved-GGUFLongCat-Flash-Lite-Sparse-Ultra-Uncensored-Heretic-Native-MTP-And-LSA-Preserved-GGUFqwen3-30b-a3b-thinking-opencode-sft-sparse-serveparityLongCat-Flash-Lite-SparseProSparse-MiniCPM-1B-sftyurts-python-code-gen-30-sparseswiglu-10Bprosparse-llama-2-7bsparsetral-16x7B-v2bloom-560m_sparsegpt_0.5DSV2-Lite-DSA-Sparse-1250Ring-mini-sparse-2.0-expgpt-neo-2.7B_sparsegpt_0.9bloom-560m_sparsegpt_0.7ReluLLaMA-7Bbloom-560m_sparsegpt_0.6bloom-560m_sparsegpt_0.8bloom-560m_sparsegpt_0.9llavaqwen3-1.7b-finetune-nm-mask-moe-sparse-4e-2k-4of8-imp-anchor_20260812_071057LongCat-Flash-Lite-Sparse-Uncensored-Heretic-Native-MTP-And-LSA-Preservedbloom-560m_sparsegpt_0.3LongCat-Flash-Lite-Sparse-Ultra-Uncensored-Heretic-Native-MTP-And-LSA-Preservedbloom-560m_sparsegpt_0.1bloom-560m_sparsegpt_0.4bloom-560m_sparsegpt_0.2llavaqwen3-1.7b-finetune-nm-mask-moe-sparse-4e-2k-1of4-imp-randrouter_20260827_200216gpt-neo-125m_sparsegpt_0.8sparsetral-16x7B-v2-SPIN_iter1gpt-neo-125m_sparsegpt_0.9sparsetral-16x7B-v2-8.0bpw-h8-exl2
