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README.md

@@ -1,3 +1,170 @@
----
-license: mit
----
+---
+quantized_by: ubergarm
+pipeline_tag: text-generation
+base_model: deepseek-ai/DeepSeek-V3.1
+license: mit
+base_model_relation: quantized
+tags:
+- mla
+- imatrix
+- deepseek_v3
+- conversational
+- ik_llama.cpp
+---
+
+Working on this currently, be patient, I may change the exact quants released depending on how they are looking. Open a discussion if you have a specific target RAM+VRAM size quant in mind for your rig.
+
+## `ik_llama.cpp` imatrix Quantizations of deepseek-ai/DeepSeek-V3.1
+This quant collection **REQUIRES** [ik_llama.cpp](https://github.com/ikawrakow/ik_llama.cpp/) fork to support the ik's latest SOTA quants and optimizations! Do **not** download these big files and expect them to run on mainline vanilla llama.cpp, ollama, LM Studio, KoboldCpp, etc!
+
+*NOTE* `ik_llama.cpp` can also run your existing GGUFs from bartowski, unsloth, mradermacher, etc if you want to try it out before downloading my quants.
+
+Some of ik's new quants are supported with [Nexesenex/croco.cpp](https://github.com/Nexesenex/croco.cpp) fork of KoboldCPP with Windows builds for CUDA 12.9. Also check for [Windows builds by Thireus here.](https://github.com/Thireus/ik_llama.cpp/releases) which have been CUDA 12.8.
+
+These quants provide best in class perplexity for the given memory footprint.
+
+## Big Thanks
+Shout out to Wendell and the **Level1Techs** crew, the community [Forums](https://forum.level1techs.com/t/deepseek-deep-dive-r1-at-home/225826), [YouTube Channel](https://www.youtube.com/@Level1Techs)!  **BIG thanks** for providing **BIG hardware** expertise and access to run these experiments and make these great quants available to the community!!!
+
+Also thanks to all the folks in the quanting and inferencing community on [BeaverAI Club Discord](https://huggingface.co/BeaverAI) and on [r/LocalLLaMA](https://www.reddit.com/r/LocalLLaMA/) for tips and tricks helping each other run, test, and benchmark all the fun new models!
+
+## Quant Collection
+Perplexity computed against *wiki.test.raw*.
+
+![Perplexity Chart](images/perplexity.png "Chart showing Perplexity improving as BPW increases.")
+
+These first two are just test quants for baseline perplexity comparison:
+* `BF16` TODO
+  - Final estimate: PPL = TODO
+
+* `Q8_0` TODO
+  - Final estimate: PPL = TODO
+
+## IQ5_K TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+echo TODO
+```
+
+</details>
+
+## IQ5_KS TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+echo TODO
+```
+
+</details>
+
+## IQ4_K TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+echo TODO
+```
+
+</details>
+
+## IQ4_KSS TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+echo TODO
+```
+
+</details>
+
+## IQ3_KS TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+echo TODO
+```
+
+</details>
+
+
+## IQ2_KL TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+echo TODO
+```
+
+</details>
+
+## IQ1_S TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+echo TODO
+```
+
+</details>
+
+## IQ1_KT TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+echo TODO
+```
+
+</details>
+
+
+## Quick Start
+```bash
+# Clone and checkout
+$ git clone https://github.com/ikawrakow/ik_llama.cpp
+$ cd ik_llama.cpp
+
+# Build for hybrid CPU+CUDA
+$ cmake -B build -DCMAKE_BUILD_TYPE=Release -DGGML_CUDA=ON -DGGML_BLAS=OFF -DGGML_SCHED_MAX_COPIES=1
+$ cmake --build build --config Release -j $(nproc)
+
+# Run API server
+$ echo TODO
+```
+
+## References
+* [ik_llama.cpp](https://github.com/ikawrakow/ik_llama.cpp)
+* [Getting Started Guide (already out of date lol)](https://github.com/ikawrakow/ik_llama.cpp/discussions/258)
+* [Quant Cookers Guide](https://github.com/ikawrakow/ik_llama.cpp/discussions/434)
+* [Compiling triton-cpu](https://github.com/triton-lang/triton-cpu/issues/237#issuecomment-2878180022)
+* [fp8 to bf16 safetensors casting without GPU](https://github.com/ggml-org/llama.cpp/issues/14762#issuecomment-3098571703)
+* [avx512 avx_vnni Zen5 experimental optimizations](https://github.com/ikawrakow/ik_llama.cpp/pull/710)
+* [ubergarm-imatrix-calibration-corpus-v02.txt](https://gist.github.com/ubergarm/edfeb3ff9c6ec8b49e88cdf627b0711a?permalink_comment_id=5682584#gistcomment-5682584)