Instructions to use SWiesmann/ThinkingCap-Qwen3.6-27B-4bit-FP16-MTPLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use SWiesmann/ThinkingCap-Qwen3.6-27B-4bit-FP16-MTPLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir ThinkingCap-Qwen3.6-27B-4bit-FP16-MTPLX SWiesmann/ThinkingCap-Qwen3.6-27B-4bit-FP16-MTPLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
ThinkingCap-Qwen3.6-27B-4bit-FP16-MTPLX
MTPLX-branded multi-token-prediction model for Apple Silicon (MLX).
Forged with MTPLX Forge from
bottlecapai/ThinkingCap-Qwen3.6-27B.
Verification
- Best depth: D2
- Multiplier vs autoregressive baseline: 1.21×
- Verified on: Apple M2 Max
- Sampler: temperature 0.6 · top_p 0.95 · top_k 20
See mtplx_runtime.json for the full verification record.
Usage
# MTPLX picks this model up automatically when downloaded:
mtplx pull <owner>/ThinkingCap-Qwen3.6-27B-4bit-FP16-MTPLX
mtplx start chat
License
See LICENSE.
- Downloads last month
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Model size
27B params
Tensor type
BF16
·
U32 ·
Hardware compatibility
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4-bit
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