Instructions to use FiditeNemini/CallMe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use FiditeNemini/CallMe with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download FiditeNemini/CallMe --local-dir CallMe
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Add CallMe voice stack: Moonshine Small Streaming (stt/), Gemma-4-E2B MLX 4-bit (llm/)
785d121 verified Download llm/processor_config.json from FiditeNemini/CallMe: direct link, hf CLI and curl.
- Browser
- Download file 598 Bytes
-
https://huggingface.co/FiditeNemini/CallMe/resolve/main/llm/processor_config.json
- Command line
-
hf download hf://FiditeNemini/CallMe/llm/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/FiditeNemini/CallMe/resolve/main/llm/processor_config.json
598 Bytes
| { | |
| "audio_seq_length": 750, | |
| "image_processor": { | |
| "do_convert_rgb": true, | |
| "do_normalize": false, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "Gemma4ImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "max_soft_tokens": 280, | |
| "patch_size": 16, | |
| "pooling_kernel_size": 3, | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 224, | |
| "width": 224 | |
| } | |
| }, | |
| "image_seq_length": 280, | |
| "processor_class": "Gemma4Processor" | |
| } | |