Instructions to use andyoneal/tweeze-lenses with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use andyoneal/tweeze-lenses with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download andyoneal/tweeze-lenses --local-dir tweeze-lenses
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
tweeze lenses
Jacobian lenses compressed for tweeze, a model-behaviour workbench running on MLX.
solarkyle-31b-q8c
solarkyle's Gemma 4 31B-IT lens (solarkyle/jspace-lenses,
gemma-4-31b-it/lens.pt at f5767d1), compressed to the layers tweeze reads, L27โL58, at 8 bits (MLX affine
quantization, group size 64). Each layer's input scale is multiplied by a power of two so that the fp16 group scales
stay out of the subnormal range. It targets block 59 and was fit on 100 WikiText-103 prompts.
solarkyle-31b-q8c/solarkyle-31b-q8c.safetensors: for each layer,L{l}.q(uint8 codes),L{l}.scalesandL{l}.biases(fp16), andL{l}.s(fp32 input scale). 983,344,936 bytes, sha2564a280218c660df60226a537dff1ee870b421e99a9b82f61b4ea7e01a43b9593e.solarkyle-31b-q8c/manifest.json: the file's sha256, the source lens's metadata, and validation figures against the fp16 lens.
At the scored layers, L28โL56 and L58, its readouts differ from the fp16 lens's in 1.84% of cells, with 1 decisive miss in 75,946. L57 is unscored.
Licensed Apache 2.0, as the source lens is.
Hardware compatibility
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