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
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Download README.md from FiditeNemini/CallMe: direct link, hf CLI and curl.
- Browser
- Download file 1.17 kB
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https://huggingface.co/FiditeNemini/CallMe/resolve/main/README.md
- Command line
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hf download hf://FiditeNemini/CallMe/README.md
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curl -L -o README.md https://huggingface.co/FiditeNemini/CallMe/resolve/main/README.md
1.17 kB
| license: other | |
| license_name: mit-and-apache-2.0 | |
| tags: [callme, mlx, moonshine, ming, on-device] | |
| # CallMe | |
| The on-device models the **CallMe AI** iPhone app downloads with **Download All Three** | |
| (Settings → Models). Each folder is one component of the voice stack. The app fetches only | |
| the files it needs, checks each large file against its SHA-256, and resumes interrupted | |
| downloads. | |
| | Folder | Component | Model | Licence | | |
| |---|---|---|---| | |
| | `stt/` | Speech recognition | [Moonshine](https://github.com/moonshine-ai/moonshine) Small Streaming (English), ONNX Runtime | MIT | | |
| | `llm/` | Conversation | [Gemma-4-E2B](https://huggingface.co/google/gemma-4-E2B-it), MLX 4-bit | [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0) | | |
| | `tts/` | Voice | [Ming-3.0-tts-0.5B](https://huggingface.co/inclusionAI/Ming-3.0-tts-0.5B), MLX Swift port, 8-bit (backbone, aggregator and DiT Linears; VAE decoder bf16) | MIT | | |
| All three are permissively licensed (MIT / Apache-2.0); see each upstream model card | |
| (Gemma 4: [model card](https://ai.google.dev/gemma/docs/core/model_card_4)). | |
| Everything runs on the phone; nothing is sent to a server during calls. | |