How to use Marvis-AI/marvis-tts-250m-v0.2-MLX-8bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Marvis-AI/marvis-tts-250m-v0.2-MLX-8bit")
# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("Marvis-AI/marvis-tts-250m-v0.2-MLX-8bit") model = AutoModelForTextToWaveform.from_pretrained("Marvis-AI/marvis-tts-250m-v0.2-MLX-8bit", device_map="auto")
How to use Marvis-AI/marvis-tts-250m-v0.2-MLX-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir marvis-tts-250m-v0.2-MLX-8bit Marvis-AI/marvis-tts-250m-v0.2-MLX-8bit
https://huggingface.co/Marvis-AI/marvis-tts-250m-v0.2-MLX-8bit/resolve/main/vocab.json
hf download hf://Marvis-AI/marvis-tts-250m-v0.2-MLX-8bit/vocab.json
curl -L -o vocab.json https://huggingface.co/Marvis-AI/marvis-tts-250m-v0.2-MLX-8bit/resolve/main/vocab.json
