q-future/Co-Instruct

1llm:2    model: 'TaylorAI/bge-micro-v2' # See Paper Sec. 3.2 and Appendix3    model_dim: 3844    embd_dim: 2565    nclasses: 7 # noise, blur, rain, haze, lol, enhancement, upsampling (Paper Sec. 4.3)6    weights: False7 8model:9    arch: "instructir"10    use_text: True11    in_ch: 312    out_ch: 313    width : 32 14    enc_blks: [2, 2, 4, 8]15    middle_blk_num: 416    dec_blks: [2, 2, 2, 2]17    textdim: 25618    weights: False19 20test:21    batch_size: 122    num_workers: 323    24    dn_datapath: "data/denoising_testsets/"25    dn_datasets: ["CBSD68", "urban100", "Kodak24", "McMaster"]26    dn_sigmas: [15, 25, 50]27 28    rain_targets: ["data/Rain/rain_test/Rain100L/target/"]29    rain_inputs:  ["data/Rain/rain_test/Rain100L/input/"]30 31    haze_targets: "data/SOTS-OUT/GT/"32    haze_inputs : "data/SOTS-OUT/IN/"33 34    lol_targets: "data/LOL/eval15/high/"35    lol_inputs : "data/LOL/eval15/low/"36 37    gopro_targets: "data/gopro_test/GoPro/target/"38    gopro_inputs: "data/gopro_test/GoPro/input/"39 40