Zero-Shot Classification
MLX
Safetensors
qwen3_5
decision-model
agents
apple-silicon
8-bit precision
Instructions to use openjev/openjev-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use openjev/openjev-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download openjev/openjev-MLX --local-dir openjev-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Place project affiliation note at the end of the README
Browse files
README.md
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The language model of [OpenJev](https://huggingface.co/openjev/openjev) converted for Apple silicon with mlx-lm (8-bit, group size 64), about 27 GB. Everything about the model, the API and the results is in the main card; this page says what this build is, how it was checked and how to run it.
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**Text only.** The converter keeps the language model and drops the vision tower, so this build answers questions about text, JSON and DOM, not screenshots.
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## Licence
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Weights: CC BY-NC 4.0 (research and non-commercial use), the same as the main repository. Helper and serving files: Apache 2.0.
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The language model of [OpenJev](https://huggingface.co/openjev/openjev) converted for Apple silicon with mlx-lm (8-bit, group size 64), about 27 GB. Everything about the model, the API and the results is in the main card; this page says what this build is, how it was checked and how to run it.
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**
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**Text only.** The converter keeps the language model and drops the vision tower, so this build answers questions about text, JSON and DOM, not screenshots.
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## Licence
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Weights: CC BY-NC 4.0 (research and non-commercial use), the same as the main repository. Helper and serving files: Apache 2.0.
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OpenJev is an independent project, not affiliated with TypeSafe; Jev is their product.
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