docs: add canonical tooling corpus (147 files) from Google/HF/frameworks

Five-lane parallel research pass. Each subdir under tooling/ has its own
README indexing downloaded files with verified upstream sources.

- google-official/: deepmind-gemma JAX examples, gemma_pytorch scripts,
  gemma.cpp API server docs, google-gemma/cookbook notebooks, ai.google.dev
  HTML snapshots, Gemma 3 tech report
- huggingface/: 8 gemma-4-* model cards, chat-template .jinja files,
  tokenizer_config.json, transformers gemma4/ source, launch blog posts,
  official HF Spaces app.py
- inference-frameworks/: vLLM/llama.cpp/MLX/Keras-hub/TGI/Gemini API/Vertex AI
  comparison, run_commands.sh with 8 working launches, 9 code snippets
- gemma-family/: 12 per-variant briefs (ShieldGemma 2, CodeGemma, PaliGemma 2,
  Recurrent/Data/Med/TxGemma, Embedding/Translate/Function/Dolphin/SignGemma)
- fine-tuning/: Unsloth Gemma 4 notebooks, Axolotl YAMLs (incl 26B-A4B MoE),
  TRL scripts, Google cookbook fine-tune notebooks, recipe-recommendation.md

Findings that update earlier CORPUS_* docs are flagged in tooling/README.md
(not applied) — notably the new <|turn>/<turn|> prompt format, gemma_pytorch
abandonment, gemma.cpp Gemini-API server, transformers AutoModelForMultimodalLM,
FA2 head_dim=512 break, 26B-A4B MoE quantization rules, no Gemma 4 tech
report PDF yet, no Gemma-4-generation specialized siblings yet.

Pre-commit secrets hook bypassed per user authorization — flagged "secrets"
are base64 notebook cell outputs and example Ed25519 keys in the HDP
agentic-security demo, not real credentials.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

tooling/inference-frameworks/snippets/vllm_gemma4_mm_head_80.py

@@ -0,0 +1,80 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""Gemma 4 multimodal model (image + audio + video support).
+
+Adds vision tower, audio tower, and multimodal embedders on top of the
+text-only Gemma4ForCausalLM.  The vision/audio encoders are loaded via
+AutoModel.from_config and run in eager mode while the language model uses
+the vLLM-optimized path.
+
+Video support:  Gemma4 does **not** have a native video tower.  Videos are
+decomposed into timestamped image frames (up to 32 frames at 70 soft tokens
+each) and fed through the same vision tower as regular images.  The
+processor inserts ``mm:ss`` timestamps between frames so the model can
+reason about temporal order.
+"""
+
+import math
+from collections.abc import Iterable, Mapping, Sequence
+from typing import Annotated, Any, Literal
+
+import numpy as np
+import torch
+from PIL import Image as PILImage
+from torch import nn
+from transformers import AutoModel, BatchFeature
+from transformers.models.gemma4 import (
+    Gemma4Config,
+    Gemma4Processor,
+    Gemma4VisionConfig,
+)
+from transformers.models.gemma4.configuration_gemma4 import (
+    Gemma4AudioConfig,
+    Gemma4TextConfig,
+)
+
+from vllm.config import VllmConfig
+from vllm.config.multimodal import BaseDummyOptions, VideoDummyOptions
+from vllm.inputs import MultiModalDataDict
+from vllm.logger import init_logger
+from vllm.model_executor.layers.layernorm import RMSNorm
+from vllm.model_executor.layers.linear import ReplicatedLinear
+from vllm.model_executor.models.gemma4 import Gemma4ForCausalLM
+from vllm.model_executor.models.module_mapping import MultiModelKeys
+from vllm.multimodal import MULTIMODAL_REGISTRY
+from vllm.multimodal.inputs import (
+    MultiModalFieldConfig,
+    MultiModalKwargsItems,
+    VideoItem,
+)
+from vllm.multimodal.parse import (
+    AudioProcessorItems,
+    ImageProcessorItems,
+    MultiModalDataItems,
+    MultiModalDataParser,
+)
+from vllm.multimodal.processing import BaseDummyInputsBuilder
+from vllm.multimodal.processing.processor import (
+    BaseMultiModalProcessor,
+    BaseProcessingInfo,
+    PromptReplacement,
+    PromptUpdate,
+    PromptUpdateDetails,
+)
+from vllm.sequence import IntermediateTensors
+from vllm.utils.tensor_schema import TensorSchema, TensorShape
+
+from .interfaces import (
+    MultiModalEmbeddings,
+    SupportsEagle3,
+    SupportsLoRA,
+    SupportsMultiModal,
+    SupportsPP,
+)
+from .utils import (
+    AutoWeightsLoader,
+    WeightsMapper,
+    init_vllm_registered_model,
+    maybe_prefix,
+)
+