92 lines
3.9 KiB
Markdown
92 lines
3.9 KiB
Markdown
# Inference stack — how llama.cpp was built and launched
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This documents the exact engine used to run **open-1b** locally, and answers the
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fair question: *is the llama.cpp build stock?* **No.**
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## Engine provenance — not stock
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| **Upstream base** | `ggerganov/llama.cpp` @ `c32d1dabe` — "tests : increase tolerance for Add fusion tests (#28691)", 2026-09-10 |
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| **Local changes** | uncommitted patches adding the **`open1b`** architecture (9 files, +299 lines) |
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| **Exported patch** | [`llama-cpp-open1b.patch`](llama-cpp-open1b.patch) |
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| **Build** | `-DGGML_VULKAN=ON -DGGML_NATIVE=ON -DCMAKE_BUILD_TYPE=Release` |
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| **Binary** | `build-vulkan/bin/llama-server` — `0.4.0-dev (build 10893, commit c32d1dabe)` |
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**Why the patch is required.** Upstream llama.cpp has no `open1b` architecture. open-1b
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is Llama-3-derived but differs in four ways that the loader/graph must know about:
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- gain-free per-head RMSNorm on Q and K before RoPE (`qk_norm`, no learnable gain);
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- RMSNorm on the **token-embedding output** (`embedding_norm`);
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- **hybrid sliding-window attention** (512-token window, full causal on the last layer of each group of 5 and on the final layer);
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- **untied** input embedding / LM head, and interleaved-pair RoPE (`LLAMA_ROPE_TYPE_NORM`).
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## Patch inventory
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| File | Change |
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| `src/models/open1b.cpp` | **new** — `llama_model_open1b`: hparams, tensor mapping, graph |
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| `src/models/models.h` | declare `llama_model_open1b` |
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| `src/llama-arch.h` / `.cpp` | add `LLM_ARCH_OPEN1B` (enum + name) |
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| `src/llama-model.cpp` | dispatch `LLM_ARCH_OPEN1B`; RoPE type `NORM` |
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| `gguf-py/gguf/constants.py` | `MODEL_ARCH.OPEN1B`, arch name, tensor list |
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| `gguf-py/gguf/tensor_mapping.py` | HF → GGUF tensor name map |
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| `conversion/__init__.py` | register the converter |
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| `conversion/open1b.py` | **new** — `Open1BModel` HF→GGUF converter |
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## Build
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```bash
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git clone https://github.com/ggerganov/llama.cpp
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cd llama.cpp
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git checkout c32d1dabe
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git apply /path/to/llama-cpp-open1b.patch
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cmake -B build-vulkan -DGGML_VULKAN=ON -DGGML_NATIVE=ON -DCMAKE_BUILD_TYPE=Release
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cmake --build build-vulkan --config Release -j
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```
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## Launch
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```bash
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setsid --fork ./build-vulkan/bin/llama-server \
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-m models/open-1b-sft-f16-go.gguf \
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--device Vulkan2 -ngl 99 -c 32768 -fa off --jinja \
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--spec-type ngram-map-k,ngram-cache \
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-t 16 --parallel 1 --alias open-1b \
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--host 127.0.0.1 --port 8085 >/tmp/open1b.log 2>&1 </dev/null &
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```
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| Flag | Why |
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| `--device Vulkan2` | a single Intel Arc B580 (Vulkan1/2/3 = the three Arc; Vulkan0 = AMD iGPU) |
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| `-ngl 99` | offload all layers |
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| `-fa off` | Flash-Attention crashes on these Arc/Vulkan builds; KV thus stays f16 |
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| `-c 32768` | requested, but capped to the model's **4096**-token context |
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| `--spec-type ngram-map-k,ngram-cache` | ~×2.4 decode on small dense models |
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| `--jinja` | use the model's chat template |
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## Pipeline
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```mermaid
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flowchart LR
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HF["HF checkpoint\nmodel.safetensors (fp32)"] --> GO["tools/hf2gguf\n(pure Go)"]
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GO --> GGUF["open-1b-sft-f16-go.gguf\n(f16, byte-identical to reference)"]
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GGUF --> LC["llama.cpp Vulkan\nupstream c32d1dabe\n+ open1b.patch"]
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LC --> GPU["Intel Arc B580\n(Vulkan2)"]
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GPU --> API["llama-server\nHTTP /completion"]
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```
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## Caveats
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- **The patch is ours and uncommitted.** It lives only in the working tree of the
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build source; `llama-cpp-open1b.patch` is its export. For reproducibility it should
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be committed and, ideally, proposed upstream.
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- **The "reference" GGUF is not an independent vendor artifact.** It was produced by
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llama.cpp's `convert_hf_to_gguf.py` **with this same Open1B patch**. Our Go converter
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reproduces it byte-for-byte — a genuine independent reimplementation of the GGUF
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serialization — but "byte-identical to the reference" means *identical to our patched
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Python path*, not to a Gensyn-published file.
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- Patch quality: written for bring-up and validated by a working inference run; not
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reviewed upstream.
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