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derkar00/mms-tuk-script-latin-adapter
mms-tuk-script-latin-adapter is a automatic speech recognition model from derkar00. Use it when you need speech turned into text. The card lists the license as cc-by-nc-4.0.
This is a lightweight 8MB adapter for Turkmen (tuk-scriptlatin) Automatic Speech Recognition, extracted from facebook/mms-1b-all.
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Updated Apr 23, 2026
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From the Hugging Face model README
This is a lightweight 8MB adapter for Turkmen (tuk-script_latin)
Automatic Speech Recognition, extracted from
facebook/mms-1b-all.
Instead of downloading the full 3.6GB model, you only need this adapter alongside the base model.
import librosa
import torch
from transformers import Wav2Vec2ForCTC, AutoProcessor
# Load base model + this adapter
processor = AutoProcessor.from_pretrained("derkar00/mms-tuk-script-latin-adapter")
model = Wav2Vec2ForCTC.from_pretrained("facebook/mms-1b-all")
processor.tokenizer.set_target_lang("tuk-script_latin")
model.load_adapter("tuk-script_latin")
model.eval()
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)
# Load audio (must be 16kHz mono)
audio, _ = librosa.load("your_audio.wav", sr=16000, mono=True)
inputs = processor(audio, sampling_rate=16000, return_tensors="pt").to(device)
with torch.no_grad():
logits = model(**inputs).logits
predicted_ids = torch.argmax(logits, dim=-1)
print(processor.decode(predicted_ids[0]))
MMS uses an adapter architecture where a single large base model (3.6GB) is shared across 1000+ languages, with small language-specific adapters (~8MB each) plugged in on top.