Instructions to use sahilchachra/Tessera-4B-Preview-optiq-5bpw-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use sahilchachra/Tessera-4B-Preview-optiq-5bpw-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Tessera-4B-Preview-optiq-5bpw-mlx sahilchachra/Tessera-4B-Preview-optiq-5bpw-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Move OptiQ sidecars under optiq/ so mlx-vlm / LM Studio don't choke on them
Thanks for publishing an OptiQ quant! Heads up on a loading issue this fixes.
Loading this model in LM Studio (or anything using mlx-vlm) can fail with Received N parameters not in model for mtp.safetensors: mlx-vlm globs every *.safetensors in the folder and strict-loads the OptiQ sidecar, which the base model has no module for.
This PR moves the OptiQ sidecar(s) (mtp.safetensors / optiq_vision.safetensors) into an optiq/ subfolder. A non-recursive *.safetensors glob doesn't descend into it, so mlx-vlm / LM Studio no longer pick them up and the language tower loads cleanly. config.json is updated to point at the new path, so mlx-optiq still finds them; mlx-lm was already unaffected.
The weights are unchanged — the files are copied server-side, not re-quantized. Fixed upstream in mlx-optiq 0.3.1 (https://pypi.org/project/mlx-optiq/0.3.1/), which is how new quants avoid this. Feel free to merge if it looks good.
Done! Thanks!