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Model: Melvin56/GLM-Z1-9B-0414-GGUF Source: Original Platform
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README.md
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README.md
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---
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license: mit
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language:
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- zh
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- en
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pipeline_tag: text-generation
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library_name: transformers
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base_model:
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- THUDM/GLM-Z1-9B-0414
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---
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# Melvin56/GLM-Z1-9B-0414-GGUF
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Original Model : [THUDM/GLM-Z1-9B-0414](https://huggingface.co/THUDM/GLM-Z1-9B-0414)
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Llama.cpp build: ced44be3 (5199)
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I used imatrix to create all these quants using this [Dataset](https://gist.github.com/bartowski1182/eb213dccb3571f863da82e99418f81e8).
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---
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# Update-02
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* [Fixed Quant] Re-quantized all quants to fix this issue. [#13099](https://github.com/ggml-org/llama.cpp/pull/13099) [#13140](https://github.com/ggml-org/llama.cpp/pull/13140)
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---
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| | CPU (AVX2) | CPU (ARM NEON) | Metal | cuBLAS | rocBLAS | SYCL | CLBlast | Vulkan | Kompute |
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| :------------ | :---------: | :------------: | :---: | :----: | :-----: | :---: | :------: | :----: | :------: |
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| K-quants | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ 🐢5 | ✅ 🐢5 | ❌ |
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| I-quants | ✅ 🐢4 | ✅ 🐢4 | ✅ 🐢4 | ✅ | ✅ | Partial¹ | ❌ | ❌ | ❌ |
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```
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✅: feature works
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🚫: feature does not work
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❓: unknown, please contribute if you can test it youself
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🐢: feature is slow
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¹: IQ3_S and IQ1_S, see #5886
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²: Only with -ngl 0
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³: Inference is 50% slower
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⁴: Slower than K-quants of comparable size
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⁵: Slower than cuBLAS/rocBLAS on similar cards
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⁶: Only q8_0 and iq4_nl
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```
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