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prepping and downloading

.gitattributes

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README.md

@@ -1,5 +1,160 @@
 ---
+quantized_by: ubergarm
+pipeline_tag: text-generation
+base_model: moonshotai/Kimi-K2-Instruct-0905
 license: other
 license_name: modified-mit
 license_link: https://huggingface.co/moonshotai/Kimi-K2-Instruct-0905/blob/main/LICENSE
+base_model_relation: quantized
+tags:
+- mla
+- imatrix
+- conversational
+- ik_llama.cpp
 ---
+
+## **WIP**
+
+- [ ] download fp8 safetensors
+- [ ] convert to bf16 GGUF
+- [ ] calculate and upload imatrix from q8_0
+- [ ] begin quantizing and releasing
+
+Open a discussion if you have a specific target RAM+VRAM in mind for your rig and I'll see what I can do given the available quants. Cheers!
+
+## `ik_llama.cpp` imatrix Quantizations of moonshotai/Kimi-K2-Instruct-0905
+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.
+
+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
+Compare with Perplexity of full size `Q8_0` TODO
+
+Final estimate: PPL = TODO
+
+![Perplexity Chart](images/perplexity.png "Chart showing Perplexity improving as BPW increases.")
+
+### `smol-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>
+
+### `IQ2_KS` 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>
+
+## Example Commands
+### Hybrid (multiple) CUDA + CPU
+```bash
+# Two CUDA devices with enough VRAM to offload more layers
+# Keep in mind Kimi-K2 starts at 1 unlike DeepSeek at 3 (first dense layers)
+./build/bin/llama-server \
+    --model "$model"\
+    --alias ubergarm/Kimi-K2-Instruct-0905 \
+    --ctx-size 32768 \
+    -ctk q8_0 \
+    -fa -fmoe \
+    -mla 3 \
+    -ngl 99 \
+    -ot "blk\.(1|2|3)\.ffn_.*=CUDA0" \
+    -ot "blk\.(4|5|6)\.ffn_.*=CUDA1" \
+    -ot exps=CPU \
+    --parallel 1 \
+    --threads 48 \
+    --threads-batch 64 \
+    --host 127.0.0.1 \
+    --port 8080
+```
+
+### CPU-Only (no GPU)
+```bash
+# compile
+cmake -B build -DGGML_CUDA=0 -DGGML_BLAS=0 -DGGML_VULKAN=0
+cmake --build build --config Release -j $(nproc)
+
+# run server
+# single CPU of a dual socket rig configured one NUMA per socket
+numactl -N 0 -m 0 \
+./build/bin/llama-server \
+    --model "$model"\
+    --alias ubergarm/Kimi-K2-Instruct-0905 \
+    --ctx-size 98304 \
+    -ctk q8_0 \
+    -fa -fmoe \
+    -mla 3 \
+    --parallel 1 \
+    --threads 128 \
+    --threads-batch 192 \
+    --numa numactl \
+    --host 127.0.0.1 \
+    --port 8080
+```
+
+## References
+* [ik_llama.cpp](https://github.com/ikawrakow/ik_llama.cpp)