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.
BRP-Malmsten-10-Layer-ModelBRP-Sochirca-CodeGPT-Py150-0.6-sparse-q-only-weights-sym-per-channelBRP-Sochirca-CodeGPT-Py150-0.6-sparse-q-only-weights-sym-per-tensorBRP-Sochirca-CodeGPT-Py150-0.6-sparse-q-only-weights-asym-per-tensorBRP-Sochirca-CodeGPT-Py150-0.6-sparse-q-all-layers-asym-per-channelBRP-Sochirca-CodeGPT-Py150-pruned-0.6-sparsityBRP-Sochirca-CodeGPT-Py150-pruned-0.7-sparsityBRP-Sochirca-CodeGPT-Py150-pruned-0.8-sparsityBRP-Sochirca-CodeGPT-Py150-0.6-sparse-q-only-weights-asym-per-channelBRP-Sochirca-CodeGPT-Py150-0.6-sparse-q-all-layers-asym-per-tensorBRP-Sochirca-CodeGPT-Py150-0.6-sparse-q-all-layers-sym-per-channelBRP-Sochirca-CodeGPT-Py150-pruned-0.4-sparsityBRP-Sochirca-CodeGPT-Py150-pruned-0.5-sparsityBRP-Sochirca-CodeGPT-Py150-pruned-0.9-sparsityBRP-Sochirca-CodeGPT-Py150-0.6-sparse-q-all-layers-sym-per-tensorBRP-Storti-CodeGPT-Py150BRP-Malmsten-12-Layer-ModelBRP-Malmsten-6-Layer-ModelBRP-Malmsten-Not-Adapted-ModelBRP-Malmsten-4-Layer-ModelBRP-Malmsten-NFTT-ModelBRP-Malmsten-Tweaked-Params-ModelBRP-Malmsten-8-Epoch-ModelBRP-Malmsten-8-Layer-Modelbrpo-16-0-474brpo-15-0-24brpo-14-0-99brpo-17-0-124brpo-12-0-149-qwen
