Upload README.md

README.md

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+---
+pipeline_tag: audio-to-audio
+tags:
+  - rvc
+  - rvc-v2
+  - applio
+  - voice-conversion
+  - retrieval-based-voice-conversion
+  - contentvec
+  - rmvpe
+  - hifigan
+  - 48khz
+  - cyberpunk-2077
+  - rogue
+---
+
+# Rogue — RVC v2 Voice Conversion Model for Applio
+
+RVC v2 voice-conversion model for **Rogue**, trained with **Applio** from extracted in-game voice audio.
+
+> **Important:** this is a **voice conversion** model, not a standalone text-to-speech model. It converts an existing speech or singing performance into the target timbre while retaining much of the source timing, phrasing, and pitch contour.
+
+## Model files
+
+The supplied Applio/RVC package contains:
+
+| File | Purpose | Size |
+|---|---|---:|
+| `rogue.pth` | RVC model weights | 57,532,660 bytes / 54.87 MiB |
+| `rogue.index` | Retrieval index used to reinforce the target timbre | 333,505,619 bytes / 318.06 MiB |
+
+The uploaded package `rogue.zip` contains both files.
+
+### SHA-256
+
+```text
+rogue.pth
+b13ed63734886b2894cd667eafa26e4e966c6aea51e4422b6ee7457a71cdc210
+
+rogue.index
+dbe27e2d354f4e690b1459a2872a7f65a4d9c9f9efadc822d361abd06264bb9e
+
+rogue.zip
+d556db0d73b0e56ee48012b8e180d2e4c19a5b3b841ae7561c409b6a26435a21
+```
+
+## Model details
+
+| Property | Value |
+|---|---|
+| Model type | Retrieval-Based Voice Conversion (RVC) |
+| RVC version | **v2** |
+| Training / inference app | **Applio** |
+| Packaged model filename | `rogue.pth` |
+| Packaged index filename | `rogue.index` |
+| Internal training model name | `mara` |
+| Target / donor voice | `rogue` |
+| Sample rate | **48,000 Hz** |
+| F0 / pitch guidance | **Enabled** |
+| Pitch extractor used for feature extraction | **RMVPE** |
+| Embedder | **ContentVec** |
+| Vocoder | **HiFi-GAN** |
+| Number of speakers | **1** |
+| Published checkpoint epoch | **200** |
+| Published checkpoint step | **26,200** |
+| Embedded dataset length | `00:35:00` |
+| Model creation timestamp | `2026-09-09T10:45:38.675607` |
+| Embedded model hash | `802d9890b58d28f51309e9db116ff921280d948615abfcbb0e9069c2fb530720` |
+
+### Naming note
+
+The original Applio training sheet uses **`mara`** as the training model name and **`rogue`** as the donor/target voice. The distributed files were packaged as **`rogue.pth`** and **`rogue.index`**. The internal metadata inside `rogue.pth` still reports `model_name: mara`.
+
+## Training dataset
+
+The supplied dataset archive was verified as:
+
+| Property | Value |
+|---|---:|
+| WAV files | **626** |
+| Total duration | **35:00.422** |
+| Sample rate | **48,000 Hz** for all 626 files |
+| Channels | **Mono** for all 626 files |
+| PCM sample width | **16-bit** for all 626 files |
+| Shortest clip | **1.210 s** |
+| Median clip | **2.900 s** |
+| Mean clip | **3.355 s** |
+| Longest clip | **11.732 s** |
+
+The archive stores the clips under:
+
+```text
+mara/
+  rogue_*.wav
+```
+
+The provided dataset contains audio files rather than a transcription dataset.
+
+### Dataset preprocessing rationale
+
+The source audio was extracted from a game rather than recorded from a microphone for this training run. The training sheet therefore keeps both **Process Effects** and **Noise Reduction** disabled. The source was already produced/mastered audio, and an additional cleanup pass could remove breath, sibilance, and other speaker-specific details useful to voice conversion.
+
+## Applio training configuration
+
+### 1. Preprocess
+
+| Setting | Value |
+|---|---|
+| Model Name | `mara` |
+| Sample Rate | `48000` |
+| Cut Preprocess | `Automatic` |
+| Chunk Length | `3.0` s |
+| Overlap Length | `0.3` s |
+| Process Effects | **OFF** |
+| Noise Reduction | **OFF** |
+| CPU Cores | Default |
+
+### 2. Extract
+
+| Setting | Value |
+|---|---|
+| Model Name | `mara` |
+| Sample Rate | `48000` |
+| Pitch Extractor / F0 | **RMVPE** |
+| Embedder Model | **ContentVec** |
+| GPU | `0` |
+
+### 3. Train
+
+| Setting | Value |
+|---|---|
+| Model Name | `mara` |
+| Sample Rate | `48000` |
+| Vocoder | **HiFi-GAN** |
+| Batch Size | **8** |
+| Configured Total Epochs | **300** |
+| Save Every Epoch | **10** |
+| Save Only Latest | **OFF** |
+| Save Every Weights | **ON** |
+| Pretrained | **ON** |
+| Cache Dataset in GPU | **OFF** |
+| GPU | `0` |
+
+### Published checkpoint vs. configured training length
+
+The training configuration was set to **300 total epochs** and to save weights every 10 epochs. However, the `rogue.pth` file published in this package identifies itself as **epoch 200, step 26,200**.
+
+For that reason, this model card describes the distributed model as the **epoch-200 checkpoint** rather than calling it a 300-epoch model.
+
+## Using the model in Applio
+
+Applio expects an RVC model to use the `.pth` weights file and, when available, the matching `.index` retrieval file.
+
+### Option 1 — Applio model downloader
+
+If `rogue.zip` is uploaded to this Hugging Face repository, its direct file URL can be used in Applio's **Download Model** panel.
+
+The URL format is:
+
+```text
+https://huggingface.co/<USERNAME>/<REPOSITORY>/resolve/main/rogue.zip
+```
+
+Replace `<USERNAME>` and `<REPOSITORY>` with the actual Hugging Face repository path.
+
+### Option 2 — Manual installation
+
+Extract `rogue.zip` and place both files in one model folder, for example:
+
+```text
+Applio/
+└── logs/
+    └── Rogue/
+        ├── rogue.pth
+        └── rogue.index
+```
+
+Then refresh the model list in Applio and select the matching `.pth` and `.index`.
+
+Official Applio model-installation documentation:
+
+https://docs.applio.org/getting-started/installing-inference-models/
+
+## Example Applio CLI inference
+
+Current Applio versions expose inference through `core.py`.
+
+Example starting point:
+
+```bash
+python core.py infer \
+  --input_path input.wav \
+  --output_path rogue_output.wav \
+  --pth_path logs/Rogue/rogue.pth \
+  --index_path logs/Rogue/rogue.index \
+  --pitch 0 \
+  --index_rate 0.75 \
+  --volume_envelope 1 \
+  --protect 0.5 \
+  --f0_method rmvpe \
+  --embedder_model contentvec
+```
+
+The inference values above are **starting values, not training parameters**. Adjust them for the source recording.
+
+Useful notes:
+
+- Keep the embedder as **ContentVec**, matching training.
+- **RMVPE** is a sensible default for this model because it was also used during feature extraction.
+- `pitch 0` preserves the source pitch by default.
+- The retrieval index can improve target-timbre similarity, but an excessively high index influence may also introduce artifacts.
+- Source audio quality, pitch range, delivery, noise, and pronunciation can materially affect the result.
+
+Official Applio CLI documentation:
+
+https://docs.applio.org/reference/cli/
+
+## Reproducing the training setup
+
+The supplied training sheet also records a headless helper command:
+
+```bash
+tools/rvc_train.sh mara
+```
+
+The recorded expected Applio outputs were:
+
+```text
+/mnt/sata/Applio/logs/mara/mara.pth
+/mnt/sata/Applio/logs/mara/*.index
+```
+
+These are local paths from the original training environment and are not required for inference after the files have been packaged.
+
+## Evaluation
+
+No formal objective evaluation results, AB listening test, benchmark scores, or reference inference samples were supplied with the uploaded files.
+
+The package therefore does **not** claim that epoch 200 is objectively superior to another saved checkpoint. Users should evaluate the model by listening on representative speech/singing inputs and tuning inference parameters for their use case.
+
+## Limitations
+
+- Trained from approximately **35 minutes** of a single target voice.
+- Training material is game dialogue, so the model may inherit characteristics of that recording, performance style, mastering, or available pitch range.
+- Voice conversion quality depends strongly on the input speaker and recording.
+- Pronunciation, emotion, singing range, very high/low pitch, background noise, and aggressive processing can reduce similarity or create artifacts.
+- No multilingual or cross-language evaluation was provided.
+- No formal quality benchmark was provided.
+- This model performs voice conversion; it does not generate speech from text on its own.
+
+## Responsible use
+
+Use the model transparently and responsibly.
+
+- Do not present generated audio as an authentic recording of the original performer or as an official game asset.
+- Do not use generated audio to mislead, defraud, harass, or impersonate someone deceptively.
+- Clearly label synthetic or voice-converted audio when context could otherwise make its origin unclear.
+- Respect applicable rights, platform rules, and local law.
+
+## Rights and redistribution
+
+The training material was extracted from game audio. This model card does **not** grant rights to the original game recordings, characters, performances, trademarks, or other underlying assets.
+
+No repository license is declared in the YAML metadata above because the supplied files did not include a license specifying what redistribution or reuse rights can be granted.
+
+If the raw dataset is going to be made public, verify that you have the right to redistribute the source audio. If you do not, a safer public repository layout is to publish the trained model package and documentation without publishing the extracted source WAV files.
+
+This is an unofficial community model and is not presented as affiliated with or endorsed by the game's developers, publishers, performers, or other rights holders.
+
+## Integrity information
+
+Additional uploaded-source checksums:
+
+```text
+rogue_datasets.zip
+e5531e041a4d3e33baca6879509c58e03d6b7524239c918d800126eeba321fff
+
+SETTINGS.txt
+5e6ba830f607c276c3cd1e1acbf0184140e0916c6f8492959df26c282db60fae
+```
+
+## Recommended Hugging Face repository layout
+
+For a compact repository that supports Applio's ZIP downloader:
+
+```text
+README.md
+rogue.zip
+SETTINGS.txt
+```
+
+If you also want people to access the two RVC files directly, you can additionally upload:
+
+```text
+rogue.pth
+rogue.index
+```
+
+Be aware that keeping both the ZIP and the extracted model files duplicates the model storage.
+
+## Frameworks and references
+
+- Applio: https://github.com/IAHispano/Applio
+- Applio documentation: https://docs.applio.org/
+- Hugging Face model cards: https://huggingface.co/docs/hub/model-cards
+
+---
+
+### Quick technical summary
+
+```text
+RVC version:       v2
+Sample rate:       48000 Hz
+Pitch guidance:    yes
+Pitch extractor:   RMVPE
+Embedder:          ContentVec
+Vocoder:           HiFi-GAN
+Dataset:           626 mono 16-bit WAV files
+Dataset duration:  35:00.422
+Batch size:        8
+Configured epochs: 300
+Published epoch:   200
+Published step:    26200
+Weights:           rogue.pth
+Index:             rogue.index
+```