Update README.md

README.md

@@ -1,126 +1,10 @@
 ---
-title: vansarah TTS
+title: vansarah TTS Demo
 emoji: 🎙️
 colorFrom: pink
 colorTo: purple
 sdk: gradio
-sdk_version: 5.42.0
+sdk_version: 4.28.3
 app_file: app.py
 pinned: false
-license: apache-2.0
-language:
-- en
-base_model:
-- yl4579/StyleTTS2-LJSpeech
-pipeline_tag: text-to-speech
----
-
-**vansarah** is an open-weight TTS model...
----
-**vansarah** is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, vansarah can be deployed anywhere from production environments to personal projects.
-
-<audio controls><source src="https://huggingface.co/mr-don88/vansarah-82M/resolve/main/samples/HEARME.wav" type="audio/wav"></audio>
-
-🐈 **GitHub**: https://github.com/mr-don88/vansarah
-
-🚀 **Demo**: https://huggingface.co/spaces/MR-DON/vansarah-tts
-
-> [!NOTE]
-> As of April 2025, the market rate of vansarah served over API is **under $1 per million characters of text input**, or under $0.06 per hour of audio output. (On average, 1000 characters of input is about 1 minute of output.) Sources: [ArtificialAnalysis/Replicate at 65 cents per M chars](https://artificialanalysis.ai/text-to-speech/model-family/vansarah#price) and [DeepInfra at 80 cents per M chars](https://deepinfra.com/mr-don88/vansarah-82M).
->
-> This is an Apache-licensed model, and vansarah has been deployed in numerous projects and commercial APIs. We welcome the deployment of the model in real use cases.
-
-> [!CAUTION]
-> Fake websites like vansarahttsai_com (snapshot: https://archive.ph/nRRnk) and vansarahtts_net (snapshot: https://archive.ph/60opa) are likely scams masquerading under the banner of a popular model.
->
-> Any website containing "vansarah" in its root domain (e.g. vansarahttsai_com, vansarahtts_net) is **NOT owned by and NOT affiliated with this model page or its author**, and attempts to imply otherwise are red flags.
-
-- [Releases](#releases)
-- [Usage](#usage)
-- [EVAL.md](https://huggingface.co/mr-don88/vansarah-82M/blob/main/EVAL.md) ↗️
-- [SAMPLES.md](https://huggingface.co/mr-don88/vansarah-82M/blob/main/SAMPLES.md) ↗️
-- [VOICES.md](https://huggingface.co/mr-don88/vansarah-82M/blob/main/VOICES.md) ↗️
-- [Model Facts](#model-facts)
-- [Training Details](#training-details)
-- [Creative Commons Attribution](#creative-commons-attribution)
-- [Acknowledgements](#acknowledgements)
-
-### Releases
-
-| Model | Published | Training Data | Langs & Voices | SHA256 |
-| ----- | --------- | ------------- | -------------- | ------ |
-| **v1.0** | **2025 Jan 27** | **Few hundred hrs** | [**8 & 54**](https://huggingface.co/mr-don88/vansarah-82M/blob/main/VOICES.md) | `496dba11` |
-| [v0.19](https://huggingface.co/mr-don88/kLegacy/tree/main/v0.19) | 2024 Dec 25 | <100 hrs | 1 & 10 | `3b0c392f` |
-
-| Training Costs | v0.19 | v1.0 | **Total** |
-| -------------- | ----- | ---- | ----- |
-| in A100 80GB GPU hours | 500 | 500 | **1000** |
-| average hourly rate | $0.80/h | $1.20/h | **$1/h** |
-| in USD | $400 | $600 | **$1000** |
-
-### Usage
-You can run this basic cell on [Google Colab](https://colab.research.google.com/). [Listen to samples](https://huggingface.co/mr-don88/vansarah-82M/blob/main/SAMPLES.md). For more languages and details, see [Advanced Usage](https://github.com/mr-don88/vansarah?tab=readme-ov-file#advanced-usage).
-```py
-!pip install -q vansarah>=0.9.2 soundfile
-!apt-get -qq -y install espeak-ng > /dev/null 2>&1
-from vansarah import KPipeline
-from IPython.display import display, Audio
-import soundfile as sf
-import torch
-pipeline = KPipeline(lang_code='a')
-text = '''
-[vansarah](/kˈOkəɹO/) is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, [vansarah](/kˈOkəɹO/) can be deployed anywhere from production environments to personal projects.
-'''
-generator = pipeline(text, voice='af_heart')
-for i, (gs, ps, audio) in enumerate(generator):
-    print(i, gs, ps)
-    display(Audio(data=audio, rate=24000, autoplay=i==0))
-    sf.write(f'{i}.wav', audio, 24000)
-```
-Under the hood, `vansarah` uses [`misaki`](https://pypi.org/project/misaki/), a G2P library at https://github.com/mr-don88/misaki
-
-### Model Facts
-
-**Architecture:**
-- StyleTTS 2: https://arxiv.org/abs/2306.07691
-- ISTFTNet: https://arxiv.org/abs/2203.02395
-- Decoder only: no diffusion, no encoder release
-
-**Architected by:** Li et al @ https://github.com/yl4579/StyleTTS2
-
-**Trained by**: `@rzvzn` on Discord
-
-**Languages:** Multiple
-
-**Model SHA256 Hash:** `496dba118d1a58f5f3db2efc88dbdc216e0483fc89fe6e47ee1f2c53f18ad1e4`
-
-### Training Details
-
-**Data:** vansarah was trained exclusively on **permissive/non-copyrighted audio data** and IPA phoneme labels. Examples of permissive/non-copyrighted audio include:
-- Public domain audio
-- Audio licensed under Apache, MIT, etc
-- Synthetic audio<sup>[1]</sup> generated by closed<sup>[2]</sup> TTS models from large providers<br/>
-[1] https://copyright.gov/ai/ai_policy_guidance.pdf<br/>
-[2] No synthetic audio from open TTS models or "custom voice clones"
-
-**Total Dataset Size:** A few hundred hours of audio
-
-**Total Training Cost:** About $1000 for 1000 hours of A100 80GB vRAM
-
-### Creative Commons Attribution
-
-The following CC BY audio was part of the dataset used to train vansarah v1.0.
-
-| Audio Data | Duration Used | License | Added to Training Set After |
-| ---------- | ------------- | ------- | --------------------------- |
-| [Koniwa](https://github.com/koniwa/koniwa) `tnc` | <1h | [CC BY 3.0](https://creativecommons.org/licenses/by/3.0/deed.ja) | v0.19 / 22 Nov 2024 |
-| [SIWIS](https://datashare.ed.ac.uk/handle/10283/2353) | <11h | [CC BY 4.0](https://datashare.ed.ac.uk/bitstream/handle/10283/2353/license_text) | v0.19 / 22 Nov 2024 |
-
-### Acknowledgements
-
-- 🛠️ [@yl4579](https://huggingface.co/yl4579) for architecting StyleTTS 2.
-- 🏆 [@Pendrokar](https://huggingface.co/Pendrokar) for adding vansarah as a contender in the TTS Spaces Arena.
-- 📊 Thank you to everyone who contributed synthetic training data.
-- ❤️ Special thanks to all compute sponsors.
-- 👾 Discord server: https://discord.gg/QuGxSWBfQy
-- 🪽 vansarah is a Japanese word that translates to "heart" or "spirit". It is also the name of an [AI in the Terminator franchise](https://terminator.fandom.com/wiki/vansarah).
+---