mtmd: add unlimited-ocr (converter, full MHA) - #24969
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* feat(detect): map unlimited-ocr / deepseek-ocr archs to the vision_ocr family Unlimited-OCR is the DeepSeek-OCR architecture; its GGUF general.architecture is "unlimited-ocr" (llama.cpp mtmd support in ggml-org/llama.cpp#24969, merged 2026-06-24). Add unlimited-ocr / deepseek-ocr / deepseek2-ocr → vision_ocr so the inspect verdict reports "supported" (deploy now) instead of needs_family. Requires a llama-server built after that merge — a serving image rebuild. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * feat(detect): honest runtime-support caveat on the inspect verdict "supported" only means a family contract exists — the node's llama-server must also be new enough to LOAD the arch, a separate gate. resolve_family now carries a runtime_note for archs whose serving support landed recently (unlimited-ocr / deepseek-ocr → "needs a llama-server built after llama.cpp#24969; rebuild the serving image if it won't load"), inspect_repo surfaces it, and the HF search panel shows it as an amber caveat under the verdict. A user isn't misled into a deploy that fails at load on an old build. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> --------- Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
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…ible) (#87) The llama-builder stage clones+builds llama.cpp in ONE cached RUN, so a plain `docker compose build serving` reuses the old llama-server even after upstream HEAD moves — a new arch (Unlimited-OCR / deepseek-ocr, ggml-org/llama.cpp#24969) never gets picked up. New optional LLAMA_REF build arg: set a commit/tag to shallow-fetch and build llama.cpp at that pin — the changed ARG busts the layer cache (forcing a rebuild) AND makes the build reproducible. Empty = current behavior (latest HEAD). Wired on the serving service (it holds the llama-server that serves deployed models) via ${LLAMA_REF:-} and documented in .env.example. Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
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Overview
to the GGUF as metadata; the decoder runs full MHA and ignores it for now.
Scope: conversion + full-MHA inference. Follow-up PR (stacked on this one) implements R-SWA in the decoder.
How to run
GGUF models: sabafallah/Unlimited-OCR-GGUF
build/bin/llama-mtmd-cli -hf sabafallah/Unlimited-OCR-GGUF:bf16 \ --image tools/mtmd/test-1.jpeg -p "document parsing." \ --chat-template deepseek-ocr \ --temp 0 --flash-attn off --no-warmup \ -n 4096 -c 16384 \ --dry-multiplier 0.8 --dry-base 1.75 --dry-allowed-length 35 \ --dry-penalty-last-n 128 --dry-sequence-breaker noneAdditional information
the decoder as full MHA.
Requirements