Instructions to use Marvis-AI/marvis-tts-100m-v0.2-MLX-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Marvis-AI/marvis-tts-100m-v0.2-MLX-6bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Marvis-AI/marvis-tts-100m-v0.2-MLX-6bit")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("Marvis-AI/marvis-tts-100m-v0.2-MLX-6bit") model = AutoModelForTextToWaveform.from_pretrained("Marvis-AI/marvis-tts-100m-v0.2-MLX-6bit", device_map="auto") - MLX
How to use Marvis-AI/marvis-tts-100m-v0.2-MLX-6bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download Marvis-AI/marvis-tts-100m-v0.2-MLX-6bit --local-dir marvis-tts-100m-v0.2-MLX-6bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 671 Bytes
d989826 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | ---
license: apache-2.0
datasets:
- amphion/Emilia-Dataset
language:
- en
- fr
- de
library_name: transformers
tags:
- mlx
- mlx-audio
- transformers
- mlx
---
# Marvis-AI/marvis-tts-100m-v0.2-MLX-6bit
This model was converted to MLX format from [`Marvis-AI/marvis-tts-100m-v0.2`](https://huggingface.co/Marvis-AI/marvis-tts-100m-v0.2) using mlx-audio version **0.2.5**.
Refer to the [original model card](https://huggingface.co/Marvis-AI/marvis-tts-100m-v0.2) for more details on the model.
## Use with mlx
```bash
pip install -U mlx-audio
```
```bash
python -m mlx_audio.tts.generate --model Marvis-AI/marvis-tts-100m-v0.2-MLX-6bit --text "Describe this image."
```
|