Audio-Text-to-Text
MLX
Safetensors
lfm3_omni
liquid
lfm3
edge
decision
classification
calibration
system-one
multimodal
vision
audio
custom_code
8-bit precision
Instructions to use LiquidAI/d1-Omni-2B-MLX-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use LiquidAI/d1-Omni-2B-MLX-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download LiquidAI/d1-Omni-2B-MLX-8bit --local-dir d1-Omni-2B-MLX-8bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download model.safetensors from LiquidAI/d1-Omni-2B-MLX-8bit: direct link, hf CLI and curl.
- Browser
- Download file 2.71 GB
-
https://huggingface.co/LiquidAI/d1-Omni-2B-MLX-8bit/resolve/main/model.safetensors
- Command line
-
hf download hf://LiquidAI/d1-Omni-2B-MLX-8bit/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/LiquidAI/d1-Omni-2B-MLX-8bit/resolve/main/model.safetensors
2.71 GB
- Xet hash:
- 1129f574c058d4a50b48a83905419916b22dc8fe276f185220d6b94adf8efbca
- Size of remote file:
- 2.71 GB
- SHA256:
- 0550199bac10df39ed0bee3f5ca5d3ccf370866b8e6ab5f739ceb05a99b7314a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.