How to use Marvis-AI/marvis-tts-250m-v0.1-transformers 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-v0.1-transformers")
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("Marvis-AI/marvis-tts-250m-v0.1-transformers") model = AutoModelForTextToWaveform.from_pretrained("Marvis-AI/marvis-tts-250m-v0.1-transformers", device_map="auto")
How to use Marvis-AI/marvis-tts-250m-v0.1-transformers with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download Marvis-AI/marvis-tts-250m-v0.1-transformers --local-dir marvis-tts-250m-v0.1-transformers
https://huggingface.co/Marvis-AI/marvis-tts-250m-v0.1-transformers/resolve/00fb9617d3840225dec5639d76e17fa92c70e219/tokenizer.json
hf download hf://Marvis-AI/marvis-tts-250m-v0.1-transformers@00fb9617d3840225dec5639d76e17fa92c70e219/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/Marvis-AI/marvis-tts-250m-v0.1-transformers/resolve/00fb9617d3840225dec5639d76e17fa92c70e219/tokenizer.json
