| --- |
| license: mit |
| tags: |
| - face-recognition |
| - face-detection |
| - face-landmarks |
| - face-expression |
| - face-age-gender |
| - gguf |
| - vision |
| library_name: gguf |
| pipeline_tag: image-classification |
| --- |
| |
| # face-api weights (gguf + safetensors) |
|
|
| Pre-trained model weights from [vladmandic/face-api](https://github.com/vladmandic/face-api) |
| at commit `189226d63aabb48cb40776fd1c453ebc0fa722f1`, converted losslessly to |
| portable **safetensors** and **gguf** (float32) formats by the |
| [`CognitiveOS-Labs/tfjs-weights-to-gguf`](https://github.com/CognitiveOS-Labs/tfjs-weights-to-gguf) |
| reproducible pipeline. |
|
|
| ## Models |
|
|
| | File | Tensors | Purpose | |
| |------|---------|---------| |
| | `tiny_face_detector_model.gguf` | 19 | Tiny face detection | |
| | `face_landmark_68_model.gguf` | 49 | 68-point landmarks | |
| | `face_landmark_68_tiny_model.gguf` | 28 | Tiny 68-point landmarks | |
| | `face_recognition_model.gguf` | 117 | Face embedding (128-d) | |
| | `ssd_mobilenetv1_model.gguf` | 151 | SSD face detection | |
| | `age_gender_model.gguf` | 51 | Age / gender | |
| | `face_expression_model.gguf` | 49 | Facial expression | |
|
|
| Every model is also provided as `.safetensors` and both formats carry a |
| `*-mapping.json` recording each tensor's name, shape, dtype, data location, |
| and the original TF.js quantization block (source traceability). |
|
|
| ## Format notes |
|
|
| - **Weights only.** The face-api repo has no `model.json` — the network |
| topologies live in its TypeScript sources under `src/`. These artifacts |
| preserve the original TF.js tensor names verbatim. |
| - All tensors are **float32** (the dequantized values produced by the TF.js |
| loader), except 15 scalar `int32` constants in `ssd_mobilenetv1_model` |
| (postprocessor shape parameters). |
| - The gguf files use **generic packing** (metadata keys |
| `general.architecture`, `general.name`, `general.source`, |
| `general.source.commit`, `general.alignment`, `general.file_type`; GGML |
| dim order; `GGML_TYPE_F32`=0, `GGML_TYPE_I32`=26). They are structurally |
| valid GGUF v3 but use a custom `general.architecture`, so llama.cpp will not |
| load them yet — a runtime for these architectures is the documented |
| follow-up (see the `face-recognition` CGP repo). |
| - Reference loaders and the full bitwise-validation suite live in the |
| [`CognitiveOS-Labs/tfjs-weights-to-gguf`](https://github.com/CognitiveOS-Labs/tfjs-weights-to-gguf) |
| repo under `scripts/`. |
|
|
| ## Consumed by |
|
|
| - [`CognitiveOS-Labs/face-recognition`](https://github.com/CognitiveOS-Labs/face-recognition) |
| — CognitiveOS patch declaring `face_recognition_model.gguf` as its remote |
| wide-model weight (downloaded at `cpm install` time). |
| - [`CognitiveOS-Labs/face-recognition-tune`](https://github.com/CognitiveOS-Labs/face-recognition-tune) |
| — `cpm tune` LoRA trainer over the frozen base weights. |
|
|
| ## Source & license |
|
|
| Weights derived from `vladmandic/face-api` (MIT), commit |
| `189226d63aabb48cb40776fd1c453ebc0fa722f1`, provided "as-is". Conversion tooling |
| in the `tfjs-weights-to-gguf` repo is MIT. |
|
|
| The recognition backbone was trained on VGGFace2-like data by the face-api |
| project; generic face recognition works out of the box, while recognizing |
| specific people is an enrollment (embedding-gallery) operation. |
|
|
