tahamajs/RR / audit /BATCH_PROCESSING_SCHEDULE.md
tahamajs's picture
|
download
raw
5.18 kB
# Batch Processing Schedule (217 Modules in Groups of 4)
Total Modules: 217
Total Groups: 55
| Group # | Batch ID | Module Count | Modules |
|:---:|:---:|:---:|---|
| 1 | `Batch_01` | 4 | `AdaptiveSVD`, `AdaptiveSpanAttention`, `AdaptiveSparseAttention`, `Galerkin` |
| 2 | `Batch_02` | 4 | `HALO`, `OH`, `Primal`, `SOAFusedAttention` |
| 3 | `Batch_03` | 4 | `SqueezingHeadsAttentionDistillationLayer`, `a3`, `aa_svd_compressor`, `aasvd` |
| 4 | `Batch_04` | 4 | `adaptive_compressor`, `adaptive_ranks`, `adaptive_span_attention`, `adaptive_sparse_attention` |
| 5 | `Batch_05` | 4 | `adaptive_svd_attention`, `adasplash`, `adasvd_compressor`, `admm_compressor` |
| 6 | `Batch_06` | 4 | `admm_pruner`, `aegis_hybrid`, `aegis_spectron_fp8`, `aegis_v1` |
| 7 | `Batch_07` | 4 | `aegis_v2`, `aegis_v3`, `aegis_v4`, `aegis_v5` |
| 8 | `Batch_08` | 4 | `aegis_v6`, `armor_pruner`, `ast_pruner`, `astro_quantizer` |
| 9 | `Batch_09` | 4 | `asvd`, `bam_umoe`, `block_transformer_hiba`, `bonsai_pruner` |
| 10 | `Batch_10` | 4 | `cachenotes_compressor`, `chela_slay`, `cluster`, `come` |
| 11 | `Batch_11` | 4 | `compot_compressor`, `compressed_attention`, `compressed_mha`, `coopq_quantizer` |
| 12 | `Batch_12` | 4 | `cosformer`, `cr_compressor`, `cur_compressor`, `cur_linear` |
| 13 | `Batch_13` | 4 | `cur_moe`, `cure`, `decay_linear_attention`, `delta_kv` |
| 14 | `Batch_14` | 4 | `direct_svd`, `dobi`, `dobi_svd`, `dynamic_entropy` |
| 15 | `Batch_15` | 4 | `dynamic_rank`, `eat`, `enlighten_compressor`, `entropy_budget_allocation` |
| 16 | `Batch_16` | 4 | `erc_svd`, `expert_choice_moe`, `factorised_matrix_state`, `faq_quantizer` |
| 17 | `Batch_17` | 4 | `flap`, `flash3`, `flash_attention3`, `flash_attention3_fp8` |
| 18 | `Batch_18` | 4 | `flat_llm`, `frandi`, `full_attention`, `fused_svd_kernel` |
| 19 | `Batch_19` | 4 | `fusion`, `fusion_attn`, `galerkin_attention`, `gated_delta_net` |
| 20 | `Batch_20` | 4 | `gated_deltanet_block`, `gated_linear_attention`, `gfws_d_compressor`, `goldfinch_ahn` |
| 21 | `Batch_21` | 4 | `gqa`, `granite_hybrid`, `grecodec`, `griffin_ssd` |
| 22 | `Batch_22` | 4 | `halo_regla`, `hamming_attention`, `hashed_linear`, `hashed_net_compressor` |
| 23 | `Batch_23` | 4 | `hgrn2_gated_deltanet`, `hgrn2_layer`, `hgrn2_outer`, `hla_attention` |
| 24 | `Batch_24` | 4 | `huffman_coder`, `hybrid_svd_layer`, `hybridkv`, `hymba_transx` |
| 25 | `Batch_25` | 4 | `infini`, `jamba`, `jamba_info`, `kda_attention` |
| 26 | `Batch_26` | 4 | `kmeans_quantize`, `kronecker_compressor`, `kronecker_linear`, `kronecker_tt_lora` |
| 27 | `Batch_27` | 4 | `kvtc`, `leka_v1`, `leka_v2`, `leka_v3` |
| 28 | `Batch_28` | 4 | `liftr`, `lillama_compressor`, `linformer_attention`, `lola_attention` |
| 29 | `Batch_29` | 4 | `lora_attention`, `lsc_compressor`, `lsh_attention`, `mamba` |
| 30 | `Batch_30` | 4 | `mamba_inject`, `mamba_shedder`, `mamba_svd_flash`, `mgie_svd` |
| 31 | `Batch_31` | 4 | `minimal_aurora`, `minimal_nova`, `minimal_prism`, `minimal_svd` |
| 32 | `Batch_32` | 4 | `minimal_svd_v2`, `mixattention_moska`, `mla_attention`, `mlorq_compressor` |
| 33 | `Batch_33` | 4 | `moba`, `modegpt`, `moe_deltakv_paged`, `nasc_attention` |
| 34 | `Batch_34` | 4 | `nexus`, `nha`, `nli_softmax`, `nmf_compressor` |
| 35 | `Batch_35` | 4 | `nsa`, `nystrom_attention`, `oats`, `optimal_subspace_projection` |
| 36 | `Batch_36` | 4 | `optimized_hybrid_attention`, `orion`, `padre_attention`, `performer_attention` |
| 37 | `Batch_37` | 4 | `phantom`, `progressive_token_pruning`, `projection_factorized_attn`, `proxsparse` |
| 38 | `Batch_38` | 4 | `proxsparse_pruner`, `pruning_utils`, `ptp`, `qcqa_attention` |
| 39 | `Batch_39` | 4 | `rala_attention`, `reap_moe`, `regla_attention`, `replace` |
| 40 | `Batch_40` | 4 | `replaceme_compressor`, `res_svd`, `roast_hashed_linear`, `rotational_slicegpt_int4` |
| 41 | `Batch_41` | 4 | `routing_attention`, `rpc`, `rpca`, `saes_svd` |
| 42 | `Batch_42` | 4 | `saes_svd_v2`, `salr`, `salt`, `samba_m3` |
| 43 | `Batch_43` | 4 | `samba_moe`, `sdrm`, `simple_ssm`, `slicegpt` |
| 44 | `Batch_44` | 4 | `slicegpt_pca`, `slim_compressor`, `smart_weighted_ensemble`, `soa_attn` |
| 45 | `Batch_45` | 4 | `soa_fused_module`, `soa_module`, `soka`, `span_expanded_attention` |
| 46 | `Batch_46` | 4 | `sparsegpt`, `spectra_v2`, `spectraformer_attention`, `spectral_mamba` |
| 47 | `Batch_47` | 4 | `spectron`, `squeezing_heads`, `squeezing_heads_distill`, `squeezing_heads_distiller` |
| 48 | `Batch_48` | 4 | `subspace_projection`, `svd_attention`, `svd_compressed`, `svd_linear_attention` |
| 49 | `Batch_49` | 4 | `svd_linear_decay`, `svd_llm_v2_attention`, `svd_mamba`, `svd_proj_attn` |
| 50 | `Batch_50` | 4 | `svd_projection_attention`, `svd_sequence_attention`, `swift_svd`, `swift_svd_act` |
| 51 | `Batch_51` | 4 | `template_attention`, `tlinformer_attention`, `token_compressed_attention`, `tomoe` |
| 52 | `Batch_52` | 4 | `tpa_attention`, `tt`, `unified_rope`, `uniql_compressor` |
| 53 | `Batch_53` | 4 | `upi_mamba`, `upi_stuffed_mamba`, `vig_attention`, `vspec` |
| 54 | `Batch_54` | 4 | `weighted_ensemble`, `wgqa`, `xattention`, `zerokv_neo` |
| 55 | `Batch_55` | 1 | `zeros_attention` |

Xet Storage Details

Size:
5.18 kB
·
Xet hash:
ace7ff0dc3456e755f67e36ffb022b905076f84fd0e04498e7623898b0568ada

Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.