Zero-Shot Classification
MLX
Safetensors
qwen3_5
decision-model
agents
apple-silicon
4-bit precision
Instructions to use openjev/openjev-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use openjev/openjev-MLX-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download openjev/openjev-MLX-4bit --local-dir openjev-MLX-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
|
Download README.md from openjev/openjev-MLX-4bit: direct link, hf CLI and curl.
- Browser
- Download file 1.8 kB
-
https://huggingface.co/openjev/openjev-MLX-4bit/resolve/main/README.md
- Command line
-
hf download hf://openjev/openjev-MLX-4bit/README.md
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curl -L -o README.md https://huggingface.co/openjev/openjev-MLX-4bit/resolve/main/README.md
1.8 kB
| license: cc-by-nc-4.0 | |
| base_model: openjev/openjev | |
| tags: | |
| - decision-model | |
| - zero-shot-classification | |
| - agents | |
| - mlx | |
| - apple-silicon | |
| - 4-bit | |
| # OpenJev, MLX 4-bit | |
| **OpenJev decisions on Apple silicon, in about 15 GB.** This text-only build uses 4-bit affine quantization with group size 64. Give it text, JSON or browser DOM, your labels and your rules. It returns a typed choice, yes/no probability or score through the same OpenJev API. | |
| Labels are supplied at request time. Each question with up to 52 options uses one forward pass. See the [main model](https://huggingface.co/openjev/openjev) for the API and available formats. | |
| ## Run it | |
| ```bash | |
| uv venv mlx --python 3.12 | |
| uv pip install --python mlx/bin/python "mlx==0.32.2" "mlx-lm==0.31.3" \ | |
| "transformers==5.17.0" "openai==3.16.2" "huggingface-hub==1.32.0" | |
| mlx/bin/hf download openjev/openjev-MLX-4bit --local-dir openjev-MLX-4bit | |
| mlx/bin/hf download openjev/openjev helper/shim.py helper/shim_mlx.py \ | |
| --revision 1c341f65bfe5d50fdb935c71e9739c9e0938d6c4 --local-dir openjev-api | |
| TOKENIZER=openjev-MLX-4bit SHIM_MODEL=openjev-MLX-4bit \ | |
| READOUT_T=0.85 READOUT_NOUL_T=1.829074 READOUT_NOUL_BIAS=0 \ | |
| READOUT_TARGETED=1 READOUT_INSTR_STYLE=pyrepr SHIM_STAGGER=1 \ | |
| mlx/bin/python openjev-api/helper/shim_mlx.py \ | |
| --helper openjev-api/helper/shim.py --model openjev-MLX-4bit --port 3000 | |
| ``` | |
| Send requests to `http://localhost:3000/v1/systemone` using the main model's examples. | |
| ## Licence | |
| Weights: CC BY-NC 4.0 for research and non-commercial use, with attribution. For a commercial licence, email [support@loopai.com](mailto:support@loopai.com). Helper code: Apache 2.0. Upstream notices are included in `NOTICE` and `LICENSE-APACHE-2.0`. | |
| OpenJev is an independent project, not affiliated with TypeSafe; Jev is their product. | |