Instructions to use mlx-community/3b-de-ft-research_release-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlx-community/3b-de-ft-research_release-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="mlx-community/3b-de-ft-research_release-4bit")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("mlx-community/3b-de-ft-research_release-4bit") model = AutoModelForMultimodalLM.from_pretrained("mlx-community/3b-de-ft-research_release-4bit") - MLX
How to use mlx-community/3b-de-ft-research_release-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir 3b-de-ft-research_release-4bit mlx-community/3b-de-ft-research_release-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
mlx-community/3b-de-ft-research_release-4bit
This model was converted to MLX format from canopylabs/3b-de-ft-research_release using mlx-vlm version 0.0.3.
Refer to the original model card for more details on the model.
Use with mlx
pip install -U mlx-audio
python -m mlx_audio.tts.generate --model mlx-community/3b-de-ft-research_release-4bit --text "Hello, world"
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Hardware compatibility
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Model tree for mlx-community/3b-de-ft-research_release-4bit
Base model
meta-llama/Llama-3.2-3B-Instruct Finetuned
canopylabs/orpheus-3b-0.1-pretrained