Instructions to use NomaDamas/v-splade-efficient-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use NomaDamas/v-splade-efficient-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download NomaDamas/v-splade-efficient-mlx --local-dir v-splade-efficient-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download processor_config.json from NomaDamas/v-splade-efficient-mlx: direct link, hf CLI and curl.
- Browser
- Download file 71 Bytes
-
https://huggingface.co/NomaDamas/v-splade-efficient-mlx/resolve/main/processor_config.json
- Command line
-
hf download hf://NomaDamas/v-splade-efficient-mlx/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/NomaDamas/v-splade-efficient-mlx/resolve/main/processor_config.json
71 Bytes
| { | |
| "image_seq_len": 64, | |
| "processor_class": "Idefics3Processor" | |
| } |