Mortdecai
eecebe7ef5
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>
56 lines
5.3 KiB
Markdown
56 lines
5.3 KiB
Markdown
# Gemma family index (as of April 2026)
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Specialized sister models Google has released alongside base Gemma. Base Gemma 4 instruct/base variants are **not** listed here — they live in the main corpus at `/home/claude/bin/gemma4-research/`.
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## Summary table
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| Variant | Base gen | Sizes | Canonical use case | HF URL |
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|---|---|---|---|---|
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| **ShieldGemma** | Gemma 2 | 2B, 9B, 27B | Text safety classification (4 harm types) | [google/shieldgemma-2b](https://huggingface.co/google/shieldgemma-2b) |
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| **ShieldGemma 2** | Gemma 3 | 4B | Image safety classification (3 categories) | [google/shieldgemma-2-4b-it](https://huggingface.co/google/shieldgemma-2-4b-it) |
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| **CodeGemma** | Gemma 1 | 2B, 7B, 7B-IT | Code completion with FIM tokens | [google/codegemma-7b](https://huggingface.co/google/codegemma-7b) |
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| **PaliGemma** | Gemma 1 | 3B | Vision-language (task-prefix prompting) | [google/paligemma-3b-mix-448](https://huggingface.co/google/paligemma-3b-mix-448) |
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| **PaliGemma 2** | Gemma 2 | 3B, 10B, 28B | Vision-language, multi-resolution | [google/paligemma2-3b-pt-448](https://huggingface.co/google/paligemma2-3b-pt-448) |
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| **RecurrentGemma** | Gemma 1 | 2B, 9B | Griffin architecture, long-context throughput | [google/recurrentgemma-9b](https://huggingface.co/google/recurrentgemma-9b) |
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| **DataGemma (RIG/RAG)** | Gemma 2 | 27B | Statistical grounding via Google Data Commons | [google/datagemma-rig-27b-it](https://huggingface.co/google/datagemma-rig-27b-it) |
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| **MedGemma 1.5** | Gemma 3 | 4B multimodal | Medical text + image comprehension (non-clinical) | [google/medgemma-1.5-4b-it](https://huggingface.co/google/medgemma-1.5-4b-it) |
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| **TxGemma** | Gemma 2 | 2B, 9B, 27B | Therapeutics/drug-discovery prediction | [google/txgemma-27b-predict](https://huggingface.co/google/txgemma-27b-predict) |
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| **DolphinGemma** | Gemma (unstated) | ~400M | Marine biology / dolphin vocalization | *Not released as of April 2026* |
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| **SignGemma** | Gemma 3-era | small on-device | ASL → English translation | *Limited preview only; no public weights as of April 2026* |
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| **TranslateGemma** | Gemma 3 | 4B, 12B, 27B | 55-language text + image translation | [google/translategemma-4b-it](https://huggingface.co/google/translategemma-4b-it) |
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| **EmbeddingGemma** | Gemma 3 (T5Gemma init) | 308M | On-device text embeddings, MRL (768/512/256/128) | [google/embeddinggemma-300m](https://huggingface.co/google/embeddinggemma-300m) |
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| **T5Gemma / T5Gemma 2** | Gemma 2 / Gemma 3 | small → 4B-4B | Encoder-decoder for summarization, translation | [google/t5gemma-2-4b-4b](https://huggingface.co/google/t5gemma-2-4b-4b) |
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| **FunctionGemma** | Gemma 3 | 270M | Function-calling specialist | [google/functiongemma-270m](https://huggingface.co/google/functiongemma-270m) |
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| **VaultGemma** | Gemma 3 | 1B | Differential-privacy-trained LLM | [google/vaultgemma-1b](https://huggingface.co/google/vaultgemma-1b) |
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| **Gemma-APS** | Gemma 2 | 2B, 7B | Abstractive proposition segmentation | — |
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| **Gemma Scope / Scope 2** | Gemma 2/3 | SAE suite | Mechanistic interpretability | [google/gemma-scope](https://huggingface.co/google/gemma-scope) |
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## Gemma 4 generation status
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**As of 2026-04-18, no specialized sister model has been re-based to Gemma 4.** Every variant in the table above is built on Gemma 1, 2, or 3. The newest specialized releases (TranslateGemma, Jan 2026; T5Gemma 2, Dec 2025) still sit on Gemma 3. This is normal for Google's cadence — sisters lag the base release by 3–6 months. Expect a MedGemma-on-Gemma-4, ShieldGemma-3-on-Gemma-4, and PaliGemma 3 over summer/fall 2026.
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## Per-variant files
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- `shieldgemma.md` — covers both ShieldGemma (text) and ShieldGemma 2 (image)
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- `codegemma.md`
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- `paligemma.md` — covers both PaliGemma and PaliGemma 2
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- `recurrentgemma.md`
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- `datagemma.md`
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- `medgemma.md`
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- `txgemma.md`
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- `dolphingemma.md`
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- `signgemma.md`
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- `translategemma.md`
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- `embeddinggemma.md`
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- `other-variants.md` — T5Gemma, FunctionGemma, VaultGemma, Gemma-APS, Gemma Scope
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## Picking a variant for homelab use
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Short read — see individual files for depth.
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- **Minecraft agent (Mortdecai):** consider `FunctionGemma` (270M) as a fast-path tool-router in front of the big `mortdecai:*` models. Today's setup uses the base `qwen35`/`mortdecai` tool calling, but FunctionGemma's 270M size makes it cheap enough to run as a gateway classifier.
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- **AI music video gen / visualizer:** `PaliGemma 2` for detailed captioning of reference frames; `ShieldGemma 2` to pre-filter generated output before publishing. Base Gemma 4 vision (tested in existing corpus) handles the "describe this image" job fine — reach for PaliGemma 2 when you need spatial grounding (detect/segment task prefixes).
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- **Family history agent:** `EmbeddingGemma` (308M) is the immediate win — small, multilingual, 100+ languages, MRL to 128d for tight indices. Pair with `TranslateGemma` if sources are in German/Polish/etc. For ingest of old scanned documents, `PaliGemma 2` + `TranslateGemma` handles image-embedded text translation.
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- **General safety pass for anything going public:** `ShieldGemma 2` for images, `ShieldGemma` (Gemma 2-based) for text. Both run comfortably on pve197's CT 105.
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- **Skip for homelab:** MedGemma (disclaimer-laden, not clinical-grade, niche), TxGemma (drug discovery, highly specialist), DolphinGemma (not released), SignGemma (limited preview, no weights).
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