mucemi

orpheus-ke-lora

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README

License: apache-2.0

Quick Start

python
from snac import SNAC
from inference import load_ke_model, synthesise
import soundfile as sf


snac_model = SNAC.from_pretrained("hubertsiuzdak/snac_24khz")
model, tokenizer, lexicon = load_ke_model("mucemi/orpheus-ke-lora")
audio = synthesise("Habari, how are you today?", model, tokenizer, lexicon, snac_model)
sf.write("output.wav", audio, 24000)

Requirements

markdown
pip install unsloth snac transformers soundfile accelerate

Details

  • Base model: Orpheus 3B (canopylabs/orpheus-3b-0.1-ft)
  • Method: LoRA (r=32, alpha=32)
  • Audio codec: SNAC 24kHz
  • Quantisation: 4-bit (bitsandbytes)
  • Training: ~45 min on Kaggle T4 GPU

Model provider

mucemi

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Base

canopylabs/orpheus-3b-0.1-ft

Adapter

this model

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