Delete assets

assets/calculate-model-hashes.py

@@ -1,23 +0,0 @@
-#!/usr/bin/env python3
-
-import hashlib
-import json
-import os
-import sys
-
-import requests
-
-import model_tools as mt
-
-MODEL_CACHE_PATH = "/tmp/audio-separator-models"
-VR_MODEL_DATA_LOCAL_PATH = f"{MODEL_CACHE_PATH}/vr_model_data.json"
-MDX_MODEL_DATA_LOCAL_PATH = f"{MODEL_CACHE_PATH}/mdx_model_data.json"
-
-MODEL_DATA_URL_PREFIX = "https://raw.githubusercontent.com/TRvlvr/application_data/main"
-VR_MODEL_DATA_URL = f"{MODEL_DATA_URL_PREFIX}/vr_model_data/model_data_new.json"
-MDX_MODEL_DATA_URL = f"{MODEL_DATA_URL_PREFIX}/mdx_model_data/model_data_new.json"
-
-OUTPUT_PATH = f"{MODEL_CACHE_PATH}/model_hashes.json"
-
-if __name__ == "__main__":
-    mt.iterate_and_hash(MODEL_CACHE_PATH)

assets/delete_duplicate_models.py

@@ -1,9 +0,0 @@
-import hashlib
-import os
-from collections import defaultdict
-
-import model_tools as mt
-
-if __name__ == "__main__":
-    print(f"Scanning directory: {os.getcwd()}")
-    mt.find_and_remove_duplicates()

assets/download_models.py

@@ -1,28 +0,0 @@
-import argparse
-import os
-
-import requests
-from huggingface_hub import snapshot_download
-
-from model_tools import download_files_from_txt, download_hf_repo
-
-REPO_OWNER = "lainlives"
-REPO_NAME = "audio-separator-models"
-repo_type = "model"
-
-
-if __name__ == "__main__":
-    token = os.getenv("HF_TOKEN")
-    repo_id = f"{REPO_OWNER}/{REPO_NAME}"
-    parser = argparse.ArgumentParser(description="Model Download Tool")
-    local_dir = os.getcwd()
-    parser.add_argument(
-        "--fromtxt",
-        action="store_true",
-        help="Download or process based on a text file instead of cloning Hugging Face repo",
-    )
-    args = parser.parse_args()
-    if args.fromtxt:
-        download_files_from_txt("assets/links.txt", local_dir)
-    else:
-        download_hf_repo(repo_id, local_dir, token)

assets/json_link_processor.py

@@ -1,8 +0,0 @@
-import json
-import os
-import urllib.request
-
-import model_tools as mt
-
-if __name__ == "__main__":
-    mt.get_links_from_json("models.json")

assets/list_duplicate_remove.py

@@ -1,7 +0,0 @@
-from model_tools import remove_duplicate_lines
-
-input_filename = "file.txt"
-output_filename = "processed_links.txt"
-
-if __name__ == "__main__":
-    remove_duplicate_lines(input_filename, output_filename)

assets/luvr5-ui/models.json

@@ -1,241 +0,0 @@
-{
-    "roformer_models": {
-        "BS-Roformer-Viperx-1297": "model_bs_roformer_ep_317_sdr_12.9755.ckpt",
-        "BS-Roformer-Viperx-1296": "model_bs_roformer_ep_368_sdr_12.9628.ckpt",
-        "BS-Roformer-Viperx-1053": "model_bs_roformer_ep_937_sdr_10.5309.ckpt",
-        "Mel-Roformer-Viperx-1143": "model_mel_band_roformer_ep_3005_sdr_11.4360.ckpt",
-        "BS-Roformer-De-Reverb": "deverb_bs_roformer_8_384dim_10depth.ckpt",
-        "Mel-Roformer-Crowd-Aufr33-Viperx": "mel_band_roformer_crowd_aufr33_viperx_sdr_8.7144.ckpt",
-        "Mel-Roformer-Denoise-Aufr33": "denoise_mel_band_roformer_aufr33_sdr_27.9959.ckpt",
-        "Mel-Roformer-Denoise-Aufr33-Aggr": "denoise_mel_band_roformer_aufr33_aggr_sdr_27.9768.ckpt",
-        "MelBand Roformer | Denoise-Debleed by Gabox": "mel_band_roformer_denoise_debleed_gabox.ckpt",
-        "Mel-Roformer-Karaoke-Aufr33-Viperx": "mel_band_roformer_karaoke_aufr33_viperx_sdr_10.1956.ckpt",
-        "MelBand Roformer | Karaoke by Gabox": "mel_band_roformer_karaoke_gabox.ckpt",
-        "MelBand Roformer | Karaoke by becruily": "mel_band_roformer_karaoke_becruily.ckpt",
-        "MelBand Roformer | Vocals by Kimberley Jensen": "vocals_mel_band_roformer.ckpt",
-        "MelBand Roformer Kim | FT by unwa": "mel_band_roformer_kim_ft_unwa.ckpt",
-        "MelBand Roformer Kim | FT 2 by unwa": "mel_band_roformer_kim_ft2_unwa.ckpt",
-        "MelBand Roformer Kim | FT 2 Bleedless by unwa": "mel_band_roformer_kim_ft2_bleedless_unwa.ckpt",
-        "MelBand Roformer Kim | FT 3 by unwa": "mel_band_roformer_kim_ft3_unwa.ckpt",
-        "MelBand Roformer Kim | Inst V1 by Unwa": "melband_roformer_inst_v1.ckpt",
-        "MelBand Roformer Kim | Inst V1 Plus by Unwa": "melband_roformer_inst_v1_plus.ckpt",
-        "MelBand Roformer Kim | Inst V1 (E) by Unwa": "melband_roformer_inst_v1e.ckpt",
-        "MelBand Roformer Kim | Inst V1 (E) Plus by Unwa": "melband_roformer_inst_v1e_plus.ckpt",
-        "MelBand Roformer Kim | Inst V2 by Unwa": "melband_roformer_inst_v2.ckpt",
-        "MelBand Roformer Kim | InstVoc Duality V1 by Unwa": "melband_roformer_instvoc_duality_v1.ckpt",
-        "MelBand Roformer Kim | InstVoc Duality V2 by Unwa": "melband_roformer_instvox_duality_v2.ckpt",
-        "MelBand Roformer | Vocals by becruily": "mel_band_roformer_vocals_becruily.ckpt",
-        "MelBand Roformer | Instrumental by becruily": "mel_band_roformer_instrumental_becruily.ckpt",
-        "MelBand Roformer | Vocals Fullness by Aname": "mel_band_roformer_vocal_fullness_aname.ckpt",
-        "BS Roformer | Vocals by Gabox": "bs_roformer_vocals_gabox.ckpt",
-        "MelBand Roformer | Vocals by Gabox": "mel_band_roformer_vocals_gabox.ckpt",
-        "MelBand Roformer | Vocals FV1 by Gabox": "mel_band_roformer_vocals_fv1_gabox.ckpt",
-        "MelBand Roformer | Vocals FV2 by Gabox": "mel_band_roformer_vocals_fv2_gabox.ckpt",
-        "MelBand Roformer | Vocals FV3 by Gabox": "mel_band_roformer_vocals_fv3_gabox.ckpt",
-        "MelBand Roformer | Vocals FV4 by Gabox": "mel_band_roformer_vocals_fv4_gabox.ckpt",
-        "MelBand Roformer | Instrumental by Gabox": "mel_band_roformer_instrumental_gabox.ckpt",
-        "MelBand Roformer | Instrumental 2 by Gabox": "mel_band_roformer_instrumental_2_gabox.ckpt",
-        "MelBand Roformer | Instrumental 3 by Gabox": "mel_band_roformer_instrumental_3_gabox.ckpt",
-        "MelBand Roformer | Instrumental Bleedless V1 by Gabox": "mel_band_roformer_instrumental_bleedless_v1_gabox.ckpt",
-        "MelBand Roformer | Instrumental Bleedless V2 by Gabox": "mel_band_roformer_instrumental_bleedless_v2_gabox.ckpt",
-        "MelBand Roformer | Instrumental Bleedless V3 by Gabox": "mel_band_roformer_instrumental_bleedless_v3_gabox.ckpt",
-        "MelBand Roformer | Instrumental Fullness V1 by Gabox": "mel_band_roformer_instrumental_fullness_v1_gabox.ckpt",
-        "MelBand Roformer | Instrumental Fullness V2 by Gabox": "mel_band_roformer_instrumental_fullness_v2_gabox.ckpt",
-        "MelBand Roformer | Instrumental Fullness V3 by Gabox": "mel_band_roformer_instrumental_fullness_v3_gabox.ckpt",
-        "MelBand Roformer | Instrumental Fullness Noisy V4 by Gabox": "mel_band_roformer_instrumental_fullness_noise_v4_gabox.ckpt",
-        "MelBand Roformer | INSTV5 by Gabox": "mel_band_roformer_instrumental_instv5_gabox.ckpt",
-        "MelBand Roformer | INSTV5N by Gabox": "mel_band_roformer_instrumental_instv5n_gabox.ckpt",
-        "MelBand Roformer | INSTV6 by Gabox": "mel_band_roformer_instrumental_instv6_gabox.ckpt",
-        "MelBand Roformer | INSTV6N by Gabox": "mel_band_roformer_instrumental_instv6n_gabox.ckpt",
-        "MelBand Roformer | INSTV7 by Gabox": "mel_band_roformer_instrumental_instv7_gabox.ckpt",
-        "MelBand Roformer | INSTV7N by Gabox": "mel_band_roformer_instrumental_instv7n_gabox.ckpt",
-        "MelBand Roformer | INSTV8 by Gabox": "mel_band_roformer_instrumental_instv8_gabox.ckpt",
-        "MelBand Roformer | INSTV8N by Gabox": "mel_band_roformer_instrumental_instv8n_gabox.ckpt",
-        "MelBand Roformer | FVX by Gabox": "mel_band_roformer_instrumental_fvx_gabox.ckpt",
-        "MelBand Roformer | De-Reverb by anvuew": "dereverb_mel_band_roformer_anvuew_sdr_19.1729.ckpt",
-        "MelBand Roformer | De-Reverb Less Aggressive by anvuew": "dereverb_mel_band_roformer_less_aggressive_anvuew_sdr_18.8050.ckpt",
-        "MelBand Roformer | De-Reverb Mono by anvuew": "dereverb_mel_band_roformer_mono_anvuew.ckpt",
-        "MelBand Roformer | De-Reverb Big by Sucial": "dereverb_big_mbr_ep_362.ckpt",
-        "MelBand Roformer | De-Reverb Super Big by Sucial": "dereverb_super_big_mbr_ep_346.ckpt",
-        "MelBand Roformer | De-Reverb-Echo by Sucial": "dereverb-echo_mel_band_roformer_sdr_10.0169.ckpt",
-        "MelBand Roformer | De-Reverb-Echo V2 by Sucial": "dereverb-echo_mel_band_roformer_sdr_13.4843_v2.ckpt",
-        "MelBand Roformer | De-Reverb-Echo Fused by Sucial": "dereverb_echo_mbr_fused.ckpt",
-        "MelBand Roformer Kim | SYHFT by SYH99999": "MelBandRoformerSYHFT.ckpt",
-        "MelBand Roformer Kim | SYHFT V2 by SYH99999": "MelBandRoformerSYHFTV2.ckpt",
-        "MelBand Roformer Kim | SYHFT V2.5 by SYH99999": "MelBandRoformerSYHFTV2.5.ckpt",
-        "MelBand Roformer Kim | SYHFT V3 by SYH99999": "MelBandRoformerSYHFTV3Epsilon.ckpt",
-        "MelBand Roformer Kim | Big SYHFT V1 by SYH99999": "MelBandRoformerBigSYHFTV1.ckpt",
-        "MelBand Roformer Kim | Big Beta 4 FT by unwa": "melband_roformer_big_beta4.ckpt",
-        "MelBand Roformer Kim | Big Beta 5e FT by unwa": "melband_roformer_big_beta5e.ckpt",
-        "MelBand Roformer | Big Beta 6 by unwa": "melband_roformer_big_beta6.ckpt",
-        "MelBand Roformer | Big Beta 6X by unwa": "melband_roformer_big_beta6x.ckpt",
-        "BS Roformer | Chorus Male-Female by Sucial": "model_chorus_bs_roformer_ep_267_sdr_24.1275.ckpt",
-        "BS Roformer | Male-Female by aufr33": "bs_roformer_male_female_by_aufr33_sdr_7.2889.ckpt",
-        "MelBand Roformer | Aspiration by Sucial": "aspiration_mel_band_roformer_sdr_18.9845.ckpt",
-        "MelBand Roformer | Aspiration Less Aggressive by Sucial": "aspiration_mel_band_roformer_less_aggr_sdr_18.1201.ckpt",
-        "MelBand Roformer | Bleed Suppressor V1 by unwa-97chris": "mel_band_roformer_bleed_suppressor_v1.ckpt",
-        "MDX23C |": "MDX23C_D1581.ckpt",
-        "MDX23C | InstVoc HQ": "MDX23C-8KFFT-InstVoc_HQ.ckpt",
-        "MDX23C | InstVoc HQ v2": "MDX23C-8KFFT-InstVoc_HQ_2.ckpt",
-        "MDX23C | De-Reverb": "MDX23C-De-Reverb-aufr33-jarredou.ckpt",
-        "MDX23C | Drum Seperator": "MDX23C-DrumSep-aufr33-jarredou.ckpt"
-    },
-    "mdx23c_models": [
-        "MDX23C_D1581.ckpt",
-        "MDX23C-8KFFT-InstVoc_HQ.ckpt",
-        "MDX23C-8KFFT-InstVoc_HQ_2.ckpt",
-        "MDX23C-De-Reverb-aufr33-jarredou.ckpt",
-        "MDX23C-DrumSep-aufr33-jarredou.ckpt",
-        "model_bs_roformer_ep_317_sdr_12.9755.ckpt",
-        "model_bs_roformer_ep_368_sdr_12.9628.ckpt",
-        "model_bs_roformer_ep_937_sdr_10.5309.ckpt",
-        "model_mel_band_roformer_ep_3005_sdr_11.4360.ckpt",
-        "deverb_bs_roformer_8_384dim_10depth.ckpt",
-        "mel_band_roformer_crowd_aufr33_viperx_sdr_8.7144.ckpt",
-        "denoise_mel_band_roformer_aufr33_sdr_27.9959.ckpt",
-        "denoise_mel_band_roformer_aufr33_aggr_sdr_27.9768.ckpt",
-        "mel_band_roformer_denoise_debleed_gabox.ckpt",
-        "mel_band_roformer_karaoke_aufr33_viperx_sdr_10.1956.ckpt",
-        "mel_band_roformer_karaoke_gabox.ckpt",
-        "mel_band_roformer_karaoke_becruily.ckpt",
-        "vocals_mel_band_roformer.ckpt",
-        "mel_band_roformer_kim_ft_unwa.ckpt",
-        "mel_band_roformer_kim_ft2_unwa.ckpt",
-        "mel_band_roformer_kim_ft2_bleedless_unwa.ckpt",
-        "mel_band_roformer_kim_ft3_unwa.ckpt",
-        "melband_roformer_inst_v1.ckpt",
-        "melband_roformer_inst_v1_plus.ckpt",
-        "melband_roformer_inst_v1e.ckpt",
-        "melband_roformer_inst_v1e_plus.ckpt",
-        "melband_roformer_inst_v2.ckpt",
-        "melband_roformer_instvoc_duality_v1.ckpt",
-        "melband_roformer_instvox_duality_v2.ckpt",
-        "mel_band_roformer_vocals_becruily.ckpt",
-        "mel_band_roformer_instrumental_becruily.ckpt",
-        "mel_band_roformer_vocal_fullness_aname.ckpt",
-        "mel_band_roformer_vocals_gabox.ckpt",
-        "mel_band_roformer_vocals_gabox.ckpt",
-        "mel_band_roformer_vocals_fv1_gabox.ckpt",
-        "mel_band_roformer_vocals_fv2_gabox.ckpt",
-        "mel_band_roformer_vocals_fv3_gabox.ckpt",
-        "mel_band_roformer_vocals_fv4_gabox.ckpt",
-        "mel_band_roformer_instrumental_gabox.ckpt",
-        "mel_band_roformer_instrumental_2_gabox.ckpt",
-        "mel_band_roformer_instrumental_3_gabox.ckpt",
-        "mel_band_roformer_instrumental_bleedless_v1_gabox.ckpt",
-        "mel_band_roformer_instrumental_bleedless_v2_gabox.ckpt",
-        "mel_band_roformer_instrumental_bleedless_v3_gabox.ckpt",
-        "mel_band_roformer_instrumental_fullness_v1_gabox.ckpt",
-        "mel_band_roformer_instrumental_fullness_v2_gabox.ckpt",
-        "mel_band_roformer_instrumental_fullness_v3_gabox.ckpt",
-        "mel_band_roformer_instrumental_fullness_noise_v4_gabox.ckpt",
-        "mel_band_roformer_instrumental_instv5_gabox.ckpt",
-        "mel_band_roformer_instrumental_instv5n_gabox.ckpt",
-        "mel_band_roformer_instrumental_instv6_gabox.ckpt",
-        "mel_band_roformer_instrumental_instv6n_gabox.ckpt",
-        "mel_band_roformer_instrumental_instv7_gabox.ckpt",
-        "mel_band_roformer_instrumental_instv7n_gabox.ckpt",
-        "mel_band_roformer_instrumental_instv8_gabox.ckpt",
-        "mel_band_roformer_instrumental_instv8n_gabox.ckpt",
-        "mel_band_roformer_instrumental_fvx_gabox.ckpt",
-        "dereverb_mel_band_roformer_anvuew_sdr_19.1729.ckpt",
-        "dereverb_mel_band_roformer_less_aggressive_anvuew_sdr_18.8050.ckpt",
-        "dereverb_mel_band_roformer_mono_anvuew.ckpt",
-        "dereverb_big_mbr_ep_362.ckpt",
-        "dereverb_super_big_mbr_ep_346.ckpt",
-        "dereverb-echo_mel_band_roformer_sdr_10.0169.ckpt",
-        "dereverb-echo_mel_band_roformer_sdr_13.4843_v2.ckpt",
-        "dereverb_echo_mbr_fused.ckpt",
-        "MelBandRoformerSYHFT.ckpt",
-        "MelBandRoformerSYHFTV2.ckpt",
-        "MelBandRoformerSYHFTV2.5.ckpt",
-        "MelBandRoformerSYHFTV3Epsilon.ckpt",
-        "MelBandRoformerBigSYHFTV1.ckpt",
-        "melband_roformer_big_beta4.ckpt",
-        "melband_roformer_big_beta5e.ckpt",
-        "melband_roformer_big_beta6.ckpt",
-        "melband_roformer_big_beta6x.ckpt",
-        "model_chorus_bs_roformer_ep_267_sdr_24.1275.ckpt",
-        "bs_roformer_male_female_by_aufr33_sdr_7.2889.ckpt",
-        "aspiration_mel_band_roformer_sdr_18.9845.ckpt",
-        "aspiration_mel_band_roformer_less_aggr_sdr_18.1201.ckpt",
-        "mel_band_roformer_bleed_suppressor_v1.ckpt"
-    ],
-    "mdxnet_models": [
-        "UVR-MDX-NET-Inst_full_292.onnx",
-        "UVR-MDX-NET_Inst_187_beta.onnx",
-        "UVR-MDX-NET_Inst_82_beta.onnx",
-        "UVR-MDX-NET_Inst_90_beta.onnx",
-        "UVR-MDX-NET_Main_340.onnx",
-        "UVR-MDX-NET_Main_390.onnx",
-        "UVR-MDX-NET_Main_406.onnx",
-        "UVR-MDX-NET_Main_427.onnx",
-        "UVR-MDX-NET_Main_438.onnx",
-        "UVR-MDX-NET-Inst_HQ_1.onnx",
-        "UVR-MDX-NET-Inst_HQ_2.onnx",
-        "UVR-MDX-NET-Inst_HQ_3.onnx",
-        "UVR-MDX-NET-Inst_HQ_4.onnx",
-        "UVR-MDX-NET-Inst_HQ_5.onnx",
-        "UVR_MDXNET_Main.onnx",
-        "UVR-MDX-NET-Inst_Main.onnx",
-        "UVR_MDXNET_1_9703.onnx",
-        "UVR_MDXNET_2_9682.onnx",
-        "UVR_MDXNET_3_9662.onnx",
-        "UVR-MDX-NET-Inst_1.onnx",
-        "UVR-MDX-NET-Inst_2.onnx",
-        "UVR-MDX-NET-Inst_3.onnx",
-        "UVR_MDXNET_KARA.onnx",
-        "UVR_MDXNET_KARA_2.onnx",
-        "UVR_MDXNET_9482.onnx",
-        "UVR-MDX-NET-Voc_FT.onnx",
-        "Kim_Vocal_1.onnx",
-        "Kim_Vocal_2.onnx",
-        "Kim_Inst.onnx",
-        "Reverb_HQ_By_FoxJoy.onnx",
-        "UVR-MDX-NET_Crowd_HQ_1.onnx",
-        "kuielab_a_vocals.onnx",
-        "kuielab_a_other.onnx",
-        "kuielab_a_bass.onnx",
-        "kuielab_a_drums.onnx",
-        "kuielab_b_vocals.onnx",
-        "kuielab_b_other.onnx",
-        "kuielab_b_bass.onnx",
-        "kuielab_b_drums.onnx"
-    ],
-    "vrarch_models": [
-        "1_HP-UVR.pth",
-        "2_HP-UVR.pth",
-        "3_HP-Vocal-UVR.pth",
-        "4_HP-Vocal-UVR.pth",
-        "5_HP-Karaoke-UVR.pth",
-        "6_HP-Karaoke-UVR.pth",
-        "7_HP2-UVR.pth",
-        "8_HP2-UVR.pth",
-        "9_HP2-UVR.pth",
-        "10_SP-UVR-2B-32000-1.pth",
-        "11_SP-UVR-2B-32000-2.pth",
-        "12_SP-UVR-3B-44100.pth",
-        "13_SP-UVR-4B-44100-1.pth",
-        "14_SP-UVR-4B-44100-2.pth",
-        "15_SP-UVR-MID-44100-1.pth",
-        "16_SP-UVR-MID-44100-2.pth",
-        "17_HP-Wind_Inst-UVR.pth",
-        "UVR-De-Echo-Aggressive.pth",
-        "UVR-De-Echo-Normal.pth",
-        "UVR-DeEcho-DeReverb.pth",
-        "UVR-De-Reverb-aufr33-jarredou.pth",
-        "UVR-DeNoise-Lite.pth",
-        "UVR-DeNoise.pth",
-        "UVR-BVE-4B_SN-44100-1.pth",
-        "MGM_HIGHEND_v4.pth",
-        "MGM_LOWEND_A_v4.pth",
-        "MGM_LOWEND_B_v4.pth",
-        "MGM_MAIN_v4.pth"
-    ],
-    "demucs_models": [
-        "htdemucs_ft.yaml",
-        "htdemucs_6s.yaml",
-        "htdemucs.yaml",
-        "hdemucs_mmi.yaml"
-    ]
-}

assets/luvr5-ui/models.txt

@@ -1,248 +0,0 @@
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_aspiration_mel_band_roformer.yaml
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_aspiration_mel_band_roformer.yaml
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_bs_roformer_instrumental_resurrection_unwa.yaml
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_bs_roformer_vocals_gabox.yaml
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_bs_roformer_vocals_resurrection_unwa.yaml
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_bs_roformer_vocals_revive_unwa.yaml
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_bs_roformer_vocals_revive_unwa.yaml
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_bs_roformer_vocals_revive_unwa.yaml
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_chorus_male_female_bs_roformer.yaml
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_chorus_male_female_bs_roformer.yaml
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_dereverb-echo_mel_band_roformer.yaml
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_dereverb-echo_mel_band_roformer_sdr_13.4843_v2.yaml
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-https://huggingface.co/lainlives/audio-separator-models/resolve/main/melband_roformer_instvox_duality_v2.ckpt
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/model_bs_roformer_ep_317_sdr_12.9755.ckpt
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/model_bs_roformer_ep_368_sdr_12.9628.ckpt
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/model_bs_roformer_ep_937_sdr_10.5309.ckpt
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/model_chorus_bs_roformer_ep_267_sdr_24.1275.ckpt
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/model_mel_band_roformer_ep_3005_sdr_11.4360.ckpt
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/vocals_mel_band_roformer.ckpt
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/Kim_Inst.onnx
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-https://huggingface.co/lainlives/audio-separator-models/resolve/main/Reverb_HQ_By_FoxJoy.onnx
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR-MDX-NET-Inst_1.onnx
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-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR-MDX-NET-Inst_HQ_4.onnx
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR-MDX-NET-Inst_HQ_5.onnx
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-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR-MDX-NET-Voc_FT.onnx
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-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR-MDX-NET_Inst_82_beta.onnx
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR-MDX-NET_Inst_90_beta.onnx
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR-MDX-NET_Main_340.onnx
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR-MDX-NET_Main_390.onnx
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-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR_MDXNET_2_9682.onnx
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR_MDXNET_3_9662.onnx
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR_MDXNET_9482.onnx
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR_MDXNET_KARA.onnx
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR_MDXNET_KARA_2.onnx
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/UVR_MDXNET_Main.onnx
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/kuielab_a_bass.onnx
-https://huggingface.co/lainlives/audio-separator-models/resolve/main/kuielab_a_drums.onnx
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assets/model_data/mdx_model_data.json

@@ -1,384 +0,0 @@
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-    "e733736763234047587931fc35322fd9": {
-        "config_yaml": "model_bs_roformer_ep_937_sdr_10.5309.yaml",
-        "is_roformer": true
-    },
-    "d789065adfd747d6f585b27b495bcdae": {
-        "config_yaml": "model_bs_roformer_ep_368_sdr_12.9628.yaml",
-        "is_roformer": true
-    }
-}

assets/model_data/vr_model_data.json

@@ -1,137 +0,0 @@
-{
-    "0d0e6d143046b0eecc41a22e60224582": {
-        "vr_model_param": "3band_44100_mid",
-        "primary_stem": "Instrumental"
-    },
-    "18b52f873021a0af556fb4ecd552bb8e": {
-        "vr_model_param": "2band_32000",
-        "primary_stem": "Instrumental"
-    },
-    "1fc66027c82b499c7d8f55f79e64cadc": {
-        "vr_model_param": "2band_32000",
-        "primary_stem": "Instrumental"
-    },
-    "2aa34fbc01f8e6d2bf509726481e7142": {
-        "vr_model_param": "4band_44100",
-        "primary_stem": "No Piano"
-    },
-    "3e18f639b11abea7361db1a4a91c2559": {
-        "vr_model_param": "4band_44100",
-        "primary_stem": "Instrumental"
-    },
-    "570b5f50054609a17741369a35007ddd": {
-        "vr_model_param": "4band_v3",
-        "primary_stem": "Instrumental"
-    },
-    "5a6e24c1b530f2dab045a522ef89b751": {
-        "vr_model_param": "1band_sr44100_hl512",
-        "primary_stem": "Instrumental"
-    },
-    "6b5916069a49be3fe29d4397ecfd73fa": {
-        "vr_model_param": "3band_44100_msb2",
-        "primary_stem": "Instrumental",
-        "is_karaoke": true
-    },
-    "74b3bc5fa2b69f29baf7839b858bc679": {
-        "vr_model_param": "4band_44100",
-        "primary_stem": "Instrumental"
-    },
-    "827213b316df36b52a1f3d04fec89369": {
-        "vr_model_param": "4band_44100",
-        "primary_stem": "Instrumental"
-    },
-    "911d4048eee7223eca4ee0efb7d29256": {
-        "vr_model_param": "4band_44100",
-        "primary_stem": "Vocals"
-    },
-    "941f3f7f0b0341f12087aacdfef644b1": {
-        "vr_model_param": "4band_v2",
-        "primary_stem": "Instrumental"
-    },
-    "a02827cf69d75781a35c0e8a327f3195": {
-        "vr_model_param": "1band_sr33075_hl384",
-        "primary_stem": "Instrumental"
-    },
-    "b165fbff113c959dba5303b74c6484bc": {
-        "vr_model_param": "3band_44100",
-        "primary_stem": "Instrumental"
-    },
-    "b5f988cd3e891dca7253bf5f0f3427c7": {
-        "vr_model_param": "4band_44100",
-        "primary_stem": "Instrumental"
-    },
-    "b99c35723bc35cb11ed14a4780006a80": {
-        "vr_model_param": "1band_sr44100_hl1024",
-        "primary_stem": "Instrumental"
-    },
-    "ba02fd25b71d620eebbdb49e18e4c336": {
-        "vr_model_param": "3band_44100_mid",
-        "primary_stem": "Instrumental"
-    },
-    "c4476ef424d8cba65f38d8d04e8514e2": {
-        "vr_model_param": "3band_44100_msb2",
-        "primary_stem": "Instrumental"
-    },
-    "da2d37b8be2972e550a409bae08335aa": {
-        "vr_model_param": "4band_44100",
-        "primary_stem": "Vocals"
-    },
-    "db57205d3133e39df8e050b435a78c80": {
-        "vr_model_param": "4band_44100",
-        "primary_stem": "Instrumental"
-    },
-    "ea83b08e32ec2303456fe50659035f69": {
-        "vr_model_param": "4band_v3",
-        "primary_stem": "Instrumental"
-    },
-    "f6ea8473ff86017b5ebd586ccacf156b": {
-        "vr_model_param": "4band_v2_sn",
-        "primary_stem": "Instrumental",
-        "is_karaoke": true
-    },
-    "fd297a61eafc9d829033f8b987c39a3d": {
-        "vr_model_param": "1band_sr32000_hl512",
-        "primary_stem": "Instrumental"
-    },
-    "0ec76fd9e65f81d8b4fbd13af4826ed8": {
-        "vr_model_param": "4band_v3",
-        "primary_stem": "No Woodwinds"
-    },
-    "0fb9249ffe4ffc38d7b16243f394c0ff": {
-        "vr_model_param": "4band_v3",
-        "primary_stem": "No Reverb"
-    },
-    "6857b2972e1754913aad0c9a1678c753": {
-        "vr_model_param": "4band_v3",
-        "primary_stem": "No Echo",
-        "nout": 48,
-        "nout_lstm": 128
-    },
-    "f200a145434efc7dcf0cd093f517ed52": {
-        "vr_model_param": "4band_v3",
-        "primary_stem": "No Echo",
-        "nout": 48,
-        "nout_lstm": 128
-    },
-    "44c55d8b5d2e3edea98c2b2bf93071c7": {
-        "vr_model_param": "4band_v3",
-        "primary_stem": "Noise",
-        "nout": 48,
-        "nout_lstm": 128
-    },
-    "51ea8c43a6928ed3c10ef5cb2707d57b": {
-        "vr_model_param": "1band_sr44100_hl1024",
-        "primary_stem": "Noise",
-        "nout": 16,
-        "nout_lstm": 128
-    },
-    "944950a9c5963a5eb70b445d67b7068a": {
-        "vr_model_param": "4band_v3_sn",
-        "primary_stem": "Vocals",
-        "nout": 64,
-        "nout_lstm": 128,
-        "is_karaoke": false,
-        "is_bv_model": true,
-        "is_bv_model_rebalanced": 0.9
-    }
-}

assets/model_tools.py

@@ -1,444 +0,0 @@
-import hashlib
-import json
-import os
-import re
-import subprocess
-import sys
-from collections import defaultdict
-from concurrent.futures import ThreadPoolExecutor
-
-import requests
-from huggingface_hub import HfApi, snapshot_download
-
-
-def extract_urls_from_file(input_filename, output_filename):
-    """
-    Extracts all URLs from an input text file and writes them to an output file.
-    """
-    # A general regular expression for finding URLs
-    # It looks for strings starting with http:// or https://, followed by non-whitespace characters
-    URL_REGEX = r"https?://\S+|www\.\S+"
-
-    try:
-        # 1. Read the contents of the input file
-        with open(input_filename, "r", encoding="utf-8") as f_in:
-            content = f_in.read()
-
-        # 2. Find all URLs in the content using re.findall()
-        urls = re.findall(URL_REGEX, content)
-
-        # Ensure only unique URLs are written by converting the list to a set and back to a list
-        unique_urls = sorted(list(set(urls)))
-
-        # 3. Write the extracted URLs to the output file, each on a new line
-        with open(output_filename, "w", encoding="utf-8") as f_out:
-            for url in unique_urls:
-                f_out.write(url + "\n")
-
-        print(
-            f"Found {len(unique_urls)} unique URLs and saved them to {output_filename}"
-        )
-
-    except FileNotFoundError:
-        print(f"Error: The file '{input_filename}' was not found.")
-    except Exception as e:
-        print(f"An error occurred: {e}")
-
-
-def remove_chars_from_file(input_filename, chars_to_remove):
-    """
-    Reads a text file, removes specified characters, and writes the changes back to the file.
-
-    Args:
-        input_filename (str): The name of the input text file.
-        chars_to_remove (list): A list of characters to be removed (e.g., [',', '"', '}']).
-    """
-    try:
-        # Read the file content
-        with open(input_filename, "r") as file:
-            content = file.read()
-
-        # Remove the characters
-        for char in chars_to_remove:
-            content = content.replace(char, "")
-
-        # Write the modified content back to the file
-        with open(input_filename, "w") as file:
-            file.write(content)
-
-        print(
-            f"Successfully removed characters {chars_to_remove} from {input_filename}"
-        )
-
-    except FileNotFoundError:
-        print(f"Error: The file '{input_filename}' was not found.")
-    except Exception as e:
-        print(f"An error occurred: {e}")
-
-
-def calculate_file_hash(filepath, block_size=65536):
-    """Calculates the SHA256 hash of a file's content."""
-    sha256 = hashlib.sha256()
-    try:
-        with open(filepath, "rb") as f:
-            while chunk := f.read(block_size):
-                sha256.update(chunk)
-    except FileNotFoundError:
-        return None  # Handle cases where a file might be deleted during the scan
-
-    return sha256.hexdigest()
-
-
-def find_and_remove_duplicates(directory="."):
-    """Finds duplicate files in the given directory and removes the one with the longer filename."""
-    hashes_to_files = defaultdict(list)
-    files_to_hash = {}
-
-    # Step 1: Hash all files in the directory
-    for filename in os.listdir(directory):
-        filepath = os.path.join(directory, filename)
-        if os.path.isfile(filepath):
-            file_hash = calculate_file_hash(filepath)
-            if file_hash:
-                hashes_to_files[file_hash].append(filepath)
-                files_to_hash[filepath] = file_hash
-
-    # Step 2: Identify duplicate groups (more than one file per hash)
-    duplicates = {h: files for h, files in hashes_to_files.items() if len(files) > 1}
-
-    if not duplicates:
-        print("No duplicate files found.")
-        return
-
-    # Step 3: Iterate over duplicates, compare filename length, and delete the longer one
-    for file_hash, file_list in duplicates.items():
-        # Sort files by filename length (ascending). The one to keep is the first item.
-        # If lengths are equal, an arbitrary one is kept.
-        files_sorted_by_length = sorted(file_list, key=len)
-        file_to_keep = files_sorted_by_length[0]
-        files_to_delete = files_sorted_by_length[1:]
-
-        print(f"\nDuplicate group (Hash: {file_hash[:10]}...):")
-        print(f"  Keeping: {file_to_keep}")
-        for file_to_delete in files_to_delete:
-            try:
-                os.remove(file_to_delete)
-                print(f"  Deleted: {file_to_delete} (longer filename)")
-            except OSError as e:
-                print(f"  Error deleting {file_to_delete}: {e}")
-
-
-def download_file(url, local_dir):
-    """Helper function to download a single file."""
-    try:
-        # Extract filename from URL (e.g., https://example.com/file.jpg -> file.jpg)
-        filename = url.split("/")[-1].split("?")[0] or "downloaded_file"
-        save_path = os.path.join(local_dir, filename)
-
-        # Download the file content
-        response = requests.get(url, stream=True, timeout=10)
-        response.raise_for_status()
-
-        with open(save_path, "wb") as f:
-            for chunk in response.iter_content(chunk_size=8192):
-                f.write(chunk)
-        return f"Successfully downloaded: {filename}"
-    except Exception as e:
-        return f"Failed to download {url}: {e}"
-
-
-def download_files_from_txt(filename, local_dir):
-    """Main function to read URLs and download them using 20 threads."""
-    # Ensure local directory exists
-    if not os.path.exists(local_dir):
-        os.makedirs(local_dir)
-
-    # Read URLs from the text file
-    with open(filename, "r") as f:
-        urls = [line.strip() for line in f if line.strip()]
-
-    # Use ThreadPoolExecutor to handle 20 downloads at a time
-    with ThreadPoolExecutor(max_workers=20) as executor:
-        # Submit all download tasks to the pool
-        results = [executor.submit(download_file, url, local_dir) for url in urls]
-
-        # Monitor results as they complete
-        for future in results:
-            print(future.result())
-
-
-def download_files_from_txt_aria(filename, local_dir):
-    command = [
-        "aria2c",
-        "--input-file",
-        filename,
-        "--dir",
-        local_dir,
-        "-c",  # Continue downloading a partially downloaded file
-        "-j",
-        "30",  # Set max concurrent downloads (adjust as needed)
-        "-x",
-        "16",  # Set max connections per server (adjust as needed)
-    ]
-    print(f"Starting downloads with aria2c in directory: {os.path.abspath(local_dir)}")
-    try:
-        # Execute the command
-        subprocess.run(
-            command,
-            check=True,
-            stdout=subprocess.PIPE,
-            stderr=subprocess.PIPE,
-            text=True,
-        )
-        print("All downloads finished successfully.")
-    except subprocess.CalledProcessError as e:
-        print(f"An error occurred during aria2c execution: {e.stderr}")
-    except Exception as e:
-        print(f"An unexpected error occurred: {e}")
-    finally:
-        # os.remove(filename)
-        print(f"Downloaded all files: {filename}")
-
-
-def download_hf_repo(repo_id, local_dir, repo_type, token):
-    if not token:
-        token = os.getenv("HF_TOKEN")
-    """
-    Downloads an entire Hugging Face repository to a specified local directory.
-    """
-    print(f"Downloading {repo_id} to {local_dir}...")
-
-    # Ensure the target directory exists
-    os.makedirs(local_dir, exist_ok=True)
-
-    # Download the snapshot
-    downloaded_path = snapshot_download(
-        repo_id=repo_id,
-        local_dir=local_dir,
-        token=token,
-        local_dir_use_symlinks=False,  # Set to False to ensure actual files are moved to local_dir
-        repo_type=repo_type,
-    )
-
-    print(f"Download complete! Files are located in: {downloaded_path}")
-    return downloaded_path
-
-
-def remove_duplicate_lines(input_file_path, output_file_path):
-    """
-    Reads lines from input_file_path, removes duplicates, and writes
-    unique lines to output_file_path while preserving order.
-    """
-    try:
-        # Use an ordered set to maintain the original file's line order.
-        # An easy way to do this in Python 3.7+ is using a dictionary's keys.
-        unique_lines_dict = {}
-        with open(input_file_path, "r") as input_file:
-            for line in input_file:
-                # Store line as a dictionary key; duplicates will be ignored
-                unique_lines_dict[line] = None
-
-        unique_lines = unique_lines_dict.keys()
-
-        with open(output_file_path, "w") as output_file:
-            # Write all unique lines to the new file
-            output_file.writelines(unique_lines)
-
-        print(f"Duplicates removed. Unique lines saved to '{output_file_path}'")
-
-    except FileNotFoundError:
-        print(f"Error: The file '{input_file_path}' was not found.")
-    except Exception as e:
-        print(f"An error occurred: {e}")
-
-
-def push_to_hf(repo_id, repo_type):
-    api = HfApi()
-
-    print(f"Uploading current directory to: {repo_id}")
-
-    # Upload everything in the current directory ('.') to the repo root
-    api.upload_folder(
-        folder_path=".",
-        repo_id=repo_id,
-        repo_type=repo_type,
-        commit_message="Initial model upload",
-    )
-    print("Upload complete!")
-
-
-def push_large_folder_to_hf(repo_id, repo_type):
-    api = HfApi()
-    print(f"Starting large folder upload to: {repo_id}")
-
-    # 3. Use upload_large_folder for resilience and speed
-    # This automatically handles multi-threading and local caching for resuming
-    api.upload_large_folder(
-        folder_path=".",
-        repo_id=repo_id,
-        repo_type=repo_type,
-        # Optional: ignore large junk files to save time
-        ignore_patterns=[
-            ".git/",
-            "__pycache__/",
-            "*.tmp",
-            ".DS_Store",
-            "*.cache",
-            "*.trash",
-        ],
-    )
-
-    print(
-        "\nUpload complete! Progress was cached locally; if it failed, just run again to resume."
-    )
-
-
-def get_model_hash(model_path):
-    """
-    Get the hash of a model file
-    """
-    # print(f"Getting hash for model at {model_path}")
-    try:
-        with open(model_path, "rb") as f:
-            f.seek(
-                -10000 * 1024, 2
-            )  # Move the file pointer 10MB before the end of the file
-            hash_result = hashlib.md5(f.read()).hexdigest()
-            # print(f"Hash for {model_path}: {hash_result}")
-            return hash_result
-    except IOError:
-        with open(model_path, "rb") as f:
-            hash_result = hashlib.md5(f.read()).hexdigest()
-            # print(f"IOError encountered, hash for {model_path}: {hash_result}")
-            return hash_result
-
-
-def download_file_if_missing(url, local_path):
-    """
-    Download a file from a URL if it doesn't exist locally
-    """
-    print(f"Checking if {local_path} needs to be downloaded from {url}")
-    if not os.path.exists(local_path):
-        print(f"Downloading {url} to {local_path}")
-        with requests.get(url, stream=True, timeout=10) as r:
-            r.raise_for_status()
-            with open(local_path, "wb") as f:
-                for chunk in r.iter_content(chunk_size=8192):
-                    f.write(chunk)
-        print(f"Downloaded {url} to {local_path}")
-    else:
-        print(f"{local_path} already exists. Skipping download.")
-
-
-def load_json_data(file_path):
-    """
-    Load JSON data from a file
-    """
-    print(f"Loading JSON data from {file_path}")
-    try:
-        with open(file_path, "r", encoding="utf-8") as file:
-            data = json.load(file)
-            print(f"Loaded JSON data successfully from {file_path}")
-            return data
-    except FileNotFoundError:
-        print(f"{file_path} not found.")
-        sys.exit(1)
-
-
-def iterate_and_hash(
-    directory,
-    vr_model_data_url,
-    mdx_model_data_url,
-    vr_model_data_local_path,
-    mdx_model_data_local_path,
-):
-    """
-    Iterate through a directory and hash all model files
-    """
-    print(f"Iterating through directory {directory} to hash model files")
-    model_files = [
-        (file, os.path.join(root, file))
-        for root, _, files in os.walk(directory)
-        for file in files
-        if file.endswith((".pth", ".onnx"))
-    ]
-
-    download_file_if_missing(vr_model_data_url, vr_model_data_local_path)
-    download_file_if_missing(mdx_model_data_url, mdx_model_data_local_path)
-
-    vr_model_data = load_json_data(vr_model_data_local_path)
-    mdx_model_data = load_json_data(mdx_model_data_local_path)
-
-    combined_model_params = {
-        **vr_model_data,
-        **mdx_model_data,
-    }
-
-    model_info_list = []
-    for file, file_path in sorted(model_files):
-        file_hash = get_model_hash(file_path)
-        model_info = {
-            "file": file,
-            "hash": file_hash,
-            "params": combined_model_params.get(file_hash, "Parameters not found"),
-        }
-        model_info_list.append(model_info)
-
-    print(f"Writing model info list to {OUTPUT_PATH}")
-    with open(OUTPUT_PATH, "w", encoding="utf-8") as json_file:
-        json.dump(model_info_list, json_file, indent=4)
-        print(f"Successfully wrote model info list to {OUTPUT_PATH}")
-
-
-def sort_links_by_extension(input_file, output_file):
-    # Define the custom priority order
-    priority = {
-        ".json": 0,
-        ".yaml": 1,
-        ".th": 2,
-        ".pth": 3,
-        ".ckpt": 4,
-        ".onnx": 5,  # Added .onnx (common typo for .onnx or .onx)
-    }
-
-    # Handle the specific user request for .onnx
-    # Example: Map .onnx to priority 5
-    # priority['.onnx'] = 5
-
-    try:
-        with open(input_file, "r") as f:
-            # Read lines and strip whitespace/newlines
-            links = [line.strip() for line in f if line.strip()]
-
-        def sort_key(link):
-            # Extract extension (case-insensitive)
-            _, ext = os.path.splitext(link.lower())
-            # Return priority index; if not in list, place at the end (index 100)
-            return priority.get(ext, 100), link
-
-        # Sort the links
-        sorted_links = sorted(links, key=sort_key)
-
-        with open(output_file, "w") as f:
-            for link in sorted_links:
-                f.write(link + "\n")
-
-        print(f"Successfully sorted links into: {output_file}")
-
-    except FileNotFoundError:
-        print(f"Error: The file '{input_file}' was not found.")
-
-
-# 1. Load the JSON data
-def get_links_from_json(file_input):
-    try:
-        with open(file_input, "r") as file:
-            data = json.load(file)
-    except FileNotFoundError:
-        print("Error: file not found.")
-        data = {}
-
-    # 2. Process and Download
-    for model_name, links in data.items():
-        if not isinstance(links, list) or len(links) == 0:
-            continue

assets/model_url_sorter.py

@@ -1,6 +0,0 @@
-import os
-
-from model_tools import sort_links_by_extension
-
-if __name__ == "__main__":
-    sort_links_by_extension("links.txt", "sorted_links.txt")

assets/process_dirtylist-txt.py

@@ -1,83 +0,0 @@
-import argparse
-import hashlib
-import json
-import os
-import re
-import subprocess
-import sys
-from collections import defaultdict
-from concurrent.futures import ThreadPoolExecutor
-
-import requests
-from huggingface_hub import HfApi, snapshot_download
-
-import model_tools as mt
-from model_tools import download_files_from_txt, download_hf_repo
-
-REPO_OWNER = "lainlives"
-REPO_NAME = "audio-separator-models"
-repo_type = "model"
-
-HF_TOKEN = os.getenv("HF_TOKEN")
-
-
-def uploadthething():
-    repo_id = f"{REPO_OWNER}/{REPO_NAME}"
-
-    parser = argparse.ArgumentParser(description="Model Upload Tool")
-    parser.add_argument(
-        "--large",
-        action="store_true",
-        help="Upload using upload-large-folder",
-    )
-    parser.add_argument(
-        "--token",
-        type=str,
-        default=HF_TOKEN,
-        dest="HF_TOKEN",
-        help=f"Your access token.",
-    )
-    args = parser.parse_args()
-    if args.large:
-        mt.push_large_folder_to_hf(repo_id, repo_type)
-    else:
-        mt.push_to_hf(repo_id, repo_type)
-
-
-def downloadthething():
-    token = os.getenv("HF_TOKEN")
-    repo_id = f"{REPO_OWNER}/{REPO_NAME}"
-    parser = argparse.ArgumentParser(description="Model Download Tool")
-    local_dir = os.getcwd()
-    parser.add_argument(
-        "--fromtxt",
-        action="store_true",
-        help="Download or process based on a text file instead of cloning Hugging Face repo",
-    )
-    args = parser.parse_args()
-    if args.fromtxt:
-        mt.download_files_from_txt("assets/links.txt", local_dir)
-    else:
-        mt.download_hf_repo(repo_id, local_dir, token)
-
-
-if __name__ == "__main__":
-    input_filename = "dirtylist.txt"
-    characters_to_remove = [",", '"', "}"]
-
-    mt.extract_links_to_txt(input_filename, "/tmp/extracted_html")
-    mt.extract_urls_from_file(input_filename, "/tmp/extracted_other")
-    with open("/tmp/extracted_urls.txt", "w") as outfile:
-        with open("/tmp/extracted_html", "r") as infile1:
-            outfile.write(infile1.read())
-        with open("/tmp/extracted_other", "r") as infile2:
-            outfile.write(infile2.read())
-    mt.remove_chars_from_file("/tmp/extracted_urls.txt", characters_to_remove)
-    mt.remove_duplicate_lines(
-        "/tmp/extracted_urls.txt", "/tmp/extracted_urls_deduped.txt"
-    )
-    mt.sort_links_by_extension(
-        "/tmp/extracted_urls_deduped.txt", "/tmp/sorted_links.txt"
-    )
-    downloadthething()
-    uploadthething()

assets/upload_models.py

@@ -1,35 +0,0 @@
-#! /usr/bin/env python3
-import argparse
-import os
-
-from huggingface_hub import HfApi
-
-import model_tools as mt
-
-REPO_OWNER = "lainlives"
-REPO_NAME = "audio-separator-models"
-repo_type = "model"
-HF_TOKEN = os.getenv("HF_TOKEN")
-
-
-if __name__ == "__main__":
-    repo_id = f"{REPO_OWNER}/{REPO_NAME}"
-
-    parser = argparse.ArgumentParser(description="Model Upload Tool")
-    parser.add_argument(
-        "--large",
-        action="store_true",
-        help="Upload using upload-large-folder",
-    )
-    parser.add_argument(
-        "--token",
-        type=str,
-        default=HF_TOKEN,
-        dest="HF_TOKEN",
-        help=f"Your access token.",
-    )
-    args = parser.parse_args()
-    if args.large:
-        mt.push_large_folder_to_hf(repo_id, repo_type)
-    else:
-        mt.push_to_hf(repo_id, repo_type)