Text Generation
cortiq
English
Chinese
cmf
quantized
q2tp
q4tp
mixed-precision
Mixture of Experts
hybrid-attention
2-bit
4-bit precision
Instructions to use infosave/GLM-5.3-Flash-cmf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- cortiq
How to use infosave/GLM-5.3-Flash-cmf with cortiq:
# one Rust binary, no additional dependencies cargo install cortiq-cli # or a prebuilt binary from github.com/infosave2007/cmf/releases hf download infosave/GLM-5.3-Flash-cmf --include "*.cmf" --local-dir . ls *.cmf # some repos ship more than one quantization
cortiq run FILE.cmf --prompt "What is the capital of France?"
cortiq serve FILE.cmf --port 8080 # OpenAI-compatible server
- Notebooks
- Google Colab
- Kaggle
Refresh GLM Q2TP and Q4TP performance evidence
Browse files
README.md
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in host memory and detects the available adapter budget. When dynamic pooling
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is enabled, routed experts use a bounded global GPU pool: resident experts run
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on the GPU, while cache misses are completed exactly on CPU and accumulated
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into the same MoE result.
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adapter use the same file on CPU.
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Useful controls:
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in host memory and detects the available adapter budget. When dynamic pooling
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is enabled, routed experts use a bounded global GPU pool: resident experts run
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| 109 |
on the GPU, while cache misses are completed exactly on CPU and accumulated
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| 110 |
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into the same MoE result. Automatic mode and systems without a supported
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adapter use the same file on CPU.
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Useful controls:
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