Model reference · open weights
MMS-TTS-THAI-FEMALE is an open-weight audio or speech model from VIZINTZOR. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | VIZINTZOR |
|---|---|
| Type | Audio & music |
| Task | Text→speech |
| Parameters (lead) | 86M |
| Released | 2025-02-21 |
| Popularity | 1k downloads / month |
| Licence | Unknown |
About
Finetune โมเดลโค้ด GitHub : https://github.com/VYNCX/finetune-local-vits
) เทรนโมเดลเสียงด้วยตัวเองบน Google Colab
ใช้งาน บน local คอมพิวเตอร์ https://github.com/VYNCX/VachanaTTS
การใช้งาน :
import torch
from transformers import VitsTokenizer, VitsModel, set_seed
import scipy
tokenizer = VitsTokenizer.from_pretrained("VIZINTZOR/MMS-TTS-THAI-FEMALEV2",cache_dir="./mms")
model = VitsModel.from_pretrained("VIZINTZOR/MMS-TTS-THAI-FEMALEV2",cache_dir="./mms")
inputs = tokenizer(text="สวัสดีค่ะ นี่คือเสียงพูดภาษาไทย", return_tensors="pt")
set_seed(456) # make deterministic
with torch.no_grad():
outputs = model(**inputs)
waveform = outputs.waveform[0]
# Convert PyTorch tensor to NumPy array
waveform_array = waveform.numpy()
scipy.io.wavfile.write("techno_output.wav", rate=model.config.sampling_rate, data=waveform_array)
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys mms-tts-thai-female for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (mms-tts-thai-female below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/audio/transcriptions \ -H "Authorization: Bearer $AXFORGE_API_KEY" \ -F model="mms-tts-thai-female" -F file=@audio.mp3
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.