monika-rvc-tests is an open-weight model from 922 RSG - CA, released under Open RAIL License. Its published files total 928.5 MB.
Test RVC models on the DDLC character Monika, via various hyperparams and datasets.
Model Card
By 922 RSG - CA, published under openrail, revision 1dc42f394851.
Test RVC models on the DDLC character Monika, via various hyperparams and datasets. Trained on augmented dataset of ~10 10 second clips Trained for ~100 epochs "Version 1" ("0" in the old numbering) Trained on augmented dataset of ~10 10 second clips (augmented via tortoise tts) Trained on smaller but better dataset of ~2 10 second clips (augmented via 11labs) Trained on augmented dataset of ~10+ 10 second clips (augmented via tortoise tts) "Version 2" ("1" in old numbering) Trained on smaller but better dataset of ~5 10 second clips (some augmented via 11labs) Even clearer quality but with slightly more artifacting than monika-test-7 (still better than pre 7th ones) "Version 2a" ("1a" in…
Read 922 RSG - CA's full model card
Test RVC models on the DDLC character Monika, via various hyperparams and datasets.
monika-test-0 (~07/2023)
- Trained on augmented dataset of ~10 10 second clips
- Trained for ~100 epochs
- RVC1
- "Version 1" ("0" in the old numbering)
monika-test-2 (~07/2023)
- Trained on augmented dataset of ~10 10 second clips (augmented via tortoise tts)
- Trained for 100 epochs
- RVC1
monika-test-4 (~07/2023)
- Trained on smaller but better dataset of ~2 10 second clips (augmented via 11labs)
- Trained for 150 epochs
- RVC1
monika-test-7 (08/22/2023)
- Trained on augmented dataset of ~10+ 10 second clips (augmented via tortoise tts)
- Trained for 60 epochs (720 steps)
- Better quality than others
- "Version 2" ("1" in old numbering)
- RVC2
monika-test-8 (08/22/2023)
- Trained on smaller but better dataset of ~5 10 second clips (some augmented via 11labs)
- Trained for 60 epochs (660 steps)
- Even clearer quality but with slightly more artifacting than monika-test-7 (still better than pre 7th ones)
- "Version 2a" ("1a" in old numbering)
- RVC2
ct-m3 (~10/2023)
- Trained on preprocessed version of dataset of ~5 10 second clips
- Trained for ~100 epochs
- Test model
- RVC1
ct-m4 (~10/2023)
- Trained on preprocessed version of dataset of ~5 10 second clips
- Trained for ~200 epochs
- Test model
- RVC1
ct-m4a (~10/2023)
- Trained on preprocessed version of dataset of ~5 10 second clips
- Trained for ~200 epochs
- "Version 4" ("3" in old numbering)
- RVC2
fused2 (~02/2024)
- Merge between ct-m3 and another model ("Sayori"-based model, with ratio of 75% to 25%)
- Somewhat clearer quality
- Yet another test model
- RVC2
fused5 (~01/2025)
- 50-50 merge between ct-m5 (~06/2024) and fused2
- In addition to merging, experiment with fine-tuning on more synthetic data which doubled preprocessed dataset size
- Sliiightly better than fused2; seems not to "break" where fused2 does, otherwise they seem almost the same
- RVC2
mm26a (2026)
- Trained on preprocessed and combined version of original dataset of ~5 10 second clips + 32 synthetic Chatterbox-generated ~10+ second raw voice clips
- Trained for 20 epochs
- RVC1
mm26e (2026)
- Trained on preprocessed and combined version of original dataset of ~5 10 second clips + 32 synthetic Chatterbox-generated ~10+ second preprocessed voice clips
- Trained for 20 epochs
- RVC1
mm26eg (2026)
- 50-50 merge between mm26e and mm26g
- RVC1
mm26f (2026)
- Trained on preprocessed and combined version of original dataset of ~5 10 second clips + 32 synthetic Chatterbox-generated ~10+ second preprocessed voice clips
- Trained for 20 epochs
- RVC2
mm26g (2026)
- Trained on best clips of original dataset + 5 synthetic Chatterbox-generated ~20+ second preprocessed voice clips
- Trained for 50 epochs
- RVC1
Identity and Version
- Repository
- 922-CA/monika-rvc-tests
- Publisher
- 922 RSG - CA
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- Not stated by the source
- Languages
- Not stated by the source
- Revision
- 1dc42f394851ea373cde5ea1e623bf4ed4427e13
- First published
- 2023-08-14
- Last updated
- 2026-10-06
Files and Weights
22 files, 928.5 MB in total. The weights are 15 files totalling 826.9 MB in pth.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| ct-m3.pth | Weights | 55.2 MB | fa6f9be5a1a1 |
| ct-m4.pth | Weights | 55.0 MB | 310887a8dd65 |
| ct-m4a.pth | Weights | 55.2 MB | 750523e2a073 |
| fused2.pth | Weights | 55.2 MB | fd3af1287093 |
| fused5.pth | Weights | 55.2 MB | 2422e660f357 |
| mm26a.pth | Weights | 55.0 MB | 6b4348e2e152 |
| mm26e.pth | Weights | 55.0 MB | 434b6453ac48 |
| mm26eg.pth | Weights | 55.0 MB | ea7d840ef90a |
| mm26f.pth | Weights | 55.2 MB | 99ffef0821a6 |
| mm26g.pth | Weights | 55.0 MB | 190991d3d418 |
| monika-test-0.pth | Weights | 55.0 MB | aeef673136a0 |
| monika-test-2.pth | Weights | 55.2 MB | c44959985b58 |
| monika-test-4.pth | Weights | 55.2 MB | 66595df48ddf |
| monika-test-7-(nmi2_e60_s720).pth | Weights | 55.2 MB | 415d13730a31 |
| monika-test-8-(nmi3_e60_s660).pth | Weights | 55.2 MB | e0dc8578717a |
| README.md | Documentation | 2.8 KB | — |
| added_IVF254_Flat_nprobe_1_ct-m5_v2.index | Other | 31.3 MB | acffac6b54b9 |
| added_IVF60_Flat_nprobe_1_ct-m4_v1.index | Other | 2.5 MB | bf95c30b0c6e |
| added_IVF60_Flat_nprobe_1_ct-m4a_v2.index | Other | 7.4 MB | c7bd519c2766 |
| monika-test-7-(nmi2_e60_s720).index | Other | 30.6 MB | ba907c8a7904 |
| monika-test-8-(nmi3_e60_s660).index | Other | 29.7 MB | 7d7ee1b5fbdf |
| .gitattributes | Repository | 2.0 KB | — |
License and Download
- License
- openrail
- Access
- Open weights, no gate
- Download size
- 826.9 MB
Released by 922 RSG - CA through its official repository on Hugging Face. Read the license.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 826.9 MB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About monika-rvc-tests
Can I use monika-rvc-tests commercially?
Yes, with conditions. monika-rvc-tests is released under Open RAIL License. Open RAIL licenses permit use, including commercial use, subject to the use-based restrictions listed in the license, which must be passed on to anyone who receives the model or a derivative.