| ---
|
| language:
|
| - en
|
| - ko
|
| tags:
|
| - gemma
|
| - gguf
|
| - lora
|
| - multimodal
|
| - image-generation
|
| - anime
|
| - danbooru
|
| - local-runtime
|
| license: other
|
| ---
|
|
|
| # GemmAnima Prototype Adapter Bundle |
|
|
| [Korean model card](HF_MODEL_CARD.ko.md) | [GitHub app source](https://github.com/raspie10032/Anima-Gemma4-Fusion-Multimodal) |
|
|
| ## Prototype Notice |
|
|
| This is a **v0.1 prototype adapter bundle** for the standalone GemmAnima app.
|
| It is published so the current local pipeline can be reproduced and tested. It
|
| is not a safety-rated assistant, not a production image model, and not a
|
| commercial-ready release.
|
|
|
| The repository intentionally contains GemmAnima adapters, projectors, bridge
|
| checkpoints, metadata, and docs only. Upstream base weights must be downloaded
|
| from their original model pages.
|
|
|
| ## Quick Summary
|
|
|
| | Area | Status |
|
| | --- | --- |
|
| | Release type | Public prototype adapter/checkpoint bundle |
|
| | Base weights | Not mirrored here |
|
| | Runtime shape | One shared Gemma GGUF plus task LoRA/adapters, Anima base weights, and bridge profiles |
|
| | Evaluation | Local smoke tests and bridge checks only |
|
| | Safety | Not safety-rated |
|
| | License posture | Adapter bundle notice plus upstream base-model restrictions |
|
|
|
| GemmAnima is a local multimodal adapter bundle that connects a Gemma/TIPO-style
|
| language and vision-tagging core to an Anima image-generation core through a
|
| HiddenStage bridge.
|
|
|
| This repository is intended for GemmAnima-owned adapters, projectors, bridge
|
| checkpoints, and runtime metadata for the standalone GemmAnima app. It is not a
|
| single monolithic model file, and it should not mirror upstream base model
|
| weights.
|
|
|
| ## Status
|
|
|
| - Release status: v0.1 public prototype adapter/checkpoint release
|
| - Safety status: not safety-rated
|
| - Evaluation status: partial smoke and bridge checks only
|
| - License status: adapter/checkpoint bundle with upstream dependency licenses;
|
| see `LICENSE_NOTICES.md`
|
| - Visibility: public adapter-only repository; upstream base model weights are
|
| not mirrored here
|
|
|
| Do not treat this prototype as a promoted production model without additional evaluation.
|
| Do not treat this adapter bundle as relicensing any upstream base model.
|
|
|
| ## Consumer Download
|
|
|
| This Hugging Face repository is the adapter/checkpoint bundle. The GitHub
|
| repository is the app/source-code surface. On a GemmAnima checkout, let the app
|
| plan or download model assets:
|
|
|
| ```powershell
|
| python -m gemmanima.cli model-download-plan --json
|
| python -m gemmanima.cli ensure-model-assets --json
|
| ```
|
|
|
| The app/source README owns local setup, GUI, development, and runtime details.
|
| This model card only describes the files published in the adapter bundle.
|
|
|
| ## Model Parts
|
|
|
| This repository should contain only the files produced or adapted by the
|
| GemmAnima project. Original base models should be downloaded from their original
|
| distribution pages and placed locally according to the standalone app
|
| configuration.
|
|
|
| ### 1. Gemma Core
|
|
|
| The Gemma Core handles chat, language-harness behavior, canonical English
|
| Danbooru tag output, and vision tagger language behavior.
|
|
|
| GemmAnima files:
|
|
|
| | File | Role | |
| | --- | --- | |
| | `text-adapter-model-f16.gguf` | Text/chat LoRA adapter | |
| | `vision-tagger-adapter-model-f16.gguf` | Vision/tagger LoRA adapter, refreshed from the mixed-pose-front v2 final prototype | |
| | `gemma4-tipo-vision.mmproj-f16.gguf` | Vision projector paired with the mixed-pose-front v2 final prototype | |
|
|
| External requirement:
|
|
|
| | File | How to obtain |
|
| | --- | --- |
|
| | `gemma-4-E2B-it-heretic-ara-custom.Q4_K_M.gguf` | Download from `mradermacher/gemma-4-E2B-it-heretic-ara-custom-GGUF`; do not mirror it here unless redistribution is explicitly permitted and intentionally chosen. |
|
|
|
| Upstream license metadata for the GGUF page currently reports `apache-2.0`.
|
|
|
| The preferred runtime shape is an upstream base GGUF loaded with GemmAnima
|
| task-specific LoRA adapters through llama.cpp `--lora`. Older fully merged GGUFs
|
| are not the preferred packaging shape.
|
|
|
| ### 2. Anima Image Core
|
|
|
| The Anima Image Core handles diffusion sampling and VAE decoding.
|
|
|
| GemmAnima files:
|
|
|
| This repository does not need to contain Anima Image Core base weights.
|
|
|
| External requirements:
|
|
|
| | File | Role |
|
| | --- | --- |
|
| | `split_files/diffusion_models/anima-base-v1.0.safetensors` | Download from `circlestone-labs/Anima` |
|
| | `split_files/vae/qwen_image_vae.safetensors` | Download from `circlestone-labs/Anima` |
|
|
|
| The upstream Anima page currently reports
|
| `circlestone-labs-non-commercial-license` and states that Anima is also subject
|
| to the NVIDIA Open Model License Agreement where applicable because it is a
|
| derivative of NVIDIA Cosmos-Predict2-2B-Text2Image.
|
|
|
| Anima text encoder weights are not part of the required standalone runtime. The
|
| current in-process renderer uses Anima-compatible tokenizer metadata
|
| (`t5xxl_ids` and `t5xxl_weights`) for conditioning shape compatibility, not the
|
| Anima text encoder weight file.
|
|
|
| Supported generation controls in the standalone app:
|
|
|
| | Type | Supported values |
|
| | --- | --- |
|
| | Sampler | `euler`, `euler_ancestral`, `dpmpp_2m`, `dpmpp_2m_sde_gpu` |
|
| | Scheduler | `normal`, `karras`, `sgm_uniform` |
|
| | Resolution presets | `1024x1024`, `832x1216`, `768x1344`, custom |
|
|
|
| ### 3. HiddenStage Bridge
|
|
|
| The HiddenStage Bridge connects Gemma hidden-state features to Anima-compatible
|
| conditioning.
|
|
|
| GemmAnima files:
|
|
|
| | File | Role |
|
| | --- | --- |
|
| | `hiddenstage-planner-adapter.safetensors` | Planner LoRA adapter |
|
| | `hiddenstage-planner-embed-vision.pt` | Planner vision embedding |
|
| | `kv_proj_hiddenstage_planner_v2.pt` | HiddenStage bridge checkpoint |
|
| | `kv_proj_text_delta_300k_from_epoch1_a0p35.pt` | Prototype default quality bridge profile used for normal image generation and style-tag prompts | |
| | `kv_proj_text_exact_v27_alpha35.pt` | Prototype bridge profile for signs, labels, captions, and readable-text prompts | |
|
|
| The standalone app routes bridge profiles automatically:
|
|
|
| | Profile | Automatic use |
|
| | --- | --- |
|
| | `balanced_pose` | Normal image-generation prompts; routed to `kv_proj_text_delta_300k_from_epoch1_a0p35.pt` | |
| | `style_artist` | Style-oriented tags and surface-token-heavy prompts; routed to `kv_proj_text_delta_300k_from_epoch1_a0p35.pt` | |
| | `text_exact` | Prompts asking for readable text, signs, labels, captions, or logos |
|
| | `legacy_mse` | Compatibility baseline and explicit override |
|
|
|
| Current local bridge metadata:
|
|
|
| | Metric | Value |
|
| | --- | --- |
|
| | Bridge validation MSE | `0.001104317136865575` |
|
| | Bridge gate | passed |
|
| | Planner eval loss | `1.0061092711985111` |
|
| | Planner eval threshold | `1.5` |
|
|
|
| These are engineering gate metrics and small local smoke tests, not a full
|
| end-user quality evaluation.
|
|
|
| ## Uploaded Files
|
|
|
| Checksums and byte sizes for every uploaded file are recorded in
|
| `adapter_manifest_v0.1.json`. The main uploaded payload is:
|
|
|
| | Directory | Files |
|
| | --- | --- |
|
| | `gemma_core/` | Text LoRA, vision/tagger LoRA, vision mmproj |
|
| | `hiddenstage_bridge/` | Planner adapter, planner vision embedding, legacy bridge, and three prototype bridge profiles |
|
| | repository root | Hugging Face model card, license notices, model source metadata, adapter manifest, version marker |
|
|
|
| ## Approximate Size
|
|
|
| This adapter repository should be much smaller than the full local runtime
|
| because original base weights are expected to come from their original pages:
|
|
|
| | Part | Approximate upload size | |
| | --- | ---: | |
| | Gemma Core adapters/projector | ~1.06 GB | |
| | HiddenStage Bridge | ~0.40 GB | |
| | Anima Image Core base weights | not uploaded here | |
| | Total uploaded here | ~1.46 GB | |
|
|
| For local runtime planning, the full standalone runtime is about 9 GB in decimal
|
| units after the user downloads the external base weights separately:
|
|
|
| | Part | Approximate size |
|
| | --- | ---: |
|
| | Gemma Core | ~4.51 GB |
|
| | Anima Image Core | ~4.44 GB |
|
| | HiddenStage Bridge | ~0.40 GB |
|
| | Total | ~9.34 GB |
|
|
|
| Exact size depends on final filenames and whether source adapters or
|
| compatibility reference models are included.
|
|
|
| ## Intended Use
|
|
|
| This bundle is intended for:
|
|
|
| - Local GemmAnima app runtime testing
|
| - Korean or English chat with an explicit language harness
|
| - Canonical English Danbooru tag output for tag requests
|
| - Chat-driven image-generation request planning
|
| - Anima image rendering through the app-controlled preset system
|
|
|
| For tag requests, output tags should remain canonical English Danbooru tags even
|
| when the user-facing chat language is Korean.
|
|
|
| ## Out of Scope
|
|
|
| This bundle is not intended as:
|
|
|
| - A general-purpose safety-filtered assistant
|
| - A fully evaluated public image-generation model
|
| - A replacement for downloading or licensing upstream base components
|
| - A license override for Gemma, Anima, NVIDIA Cosmos, or any source dataset
|
| - A guarantee of pose, anatomy, text rendering, or prompt fidelity
|
|
|
| ## Known Limitations
|
|
|
| - Safety and content behavior have not been fully evaluated.
|
| - Pose understanding remains an active improvement area.
|
| - Some broad ComfyUI samplers were intentionally not exposed because they were
|
| not part of the app-supported smoke-tested subset.
|
| - The app currently owns a curated sampler/scheduler contract rather than
|
| exposing every option from ComfyUI.
|
| - Bridge profile checkpoints are prototype routing choices and should not be
|
| promoted without separate evaluation.
|
| - Base model files are external dependencies and should remain linked to their
|
| original distribution pages.
|
|
|
| ## Runtime Notes
|
|
|
| Recommended local runtime:
|
|
|
| - Windows + PowerShell
|
| - RTX 4070 Ti SUPER as the primary PyTorch/rendering GPU
|
| - llama.cpp CUDA build for Gemma Core inference
|
| - GemmAnima standalone app for orchestration
|
|
|
| Keep RTX 5060 out of PyTorch cache/training paths unless explicitly re-enabled
|
| with a compatible PyTorch build.
|
|
|
| ## Release Checklist
|
|
|
| For this v0.1 public prototype adapter-only release:
|
|
|
| - The repository remains adapter/checkpoint-only.
|
| - Upstream base weights are referenced, not mirrored.
|
| - `LICENSE_NOTICES.md` is included.
|
| - SHA256 checksums are recorded in `adapter_manifest_v0.1.json`.
|
|
|
| Still required before promotion:
|
|
|
| - Run and publish a small reproducible inference smoke.
|
| - Run a safety and content-policy review.
|
| - Add representative example outputs only after evaluation.
|
|
|
| ## Example File Layout
|
|
|
| ```text
|
| .
|
| |-- README.md
|
| |-- LICENSE_NOTICES.md
|
| |-- model_sources.json
|
| |-- adapter_manifest_v0.1.json
|
| |-- gemma_core/
|
| | |-- text-adapter-model-f16.gguf
|
| | |-- vision-tagger-adapter-model-f16.gguf
|
| | `-- gemma4-tipo-vision.mmproj-f16.gguf
|
| `-- hiddenstage_bridge/
|
| |-- hiddenstage-planner-adapter.safetensors
|
| |-- hiddenstage-planner-embed-vision.pt
|
| |-- kv_proj_hiddenstage_planner_v2.pt
|
| |-- kv_proj_text_delta_300k_from_epoch1_a0p35.pt |
| `-- kv_proj_text_exact_v27_alpha35.pt |
| ```
|
|
|
| External base weights should be downloaded separately from their original model
|
| pages and referenced by the local GemmAnima app configuration.
|
|
|
| The standalone app download plan uses:
|
|
|
| ```powershell
|
| python -m gemmanima.cli model-download-plan --json
|
| python -m gemmanima.cli ensure-model-assets --json
|
| ```
|
|
|
| ## Citation and Attribution
|
|
|
| This is a composite adapter/checkpoint bundle. It does not relicense upstream
|
| base models. Add upstream citations, original download links, and license
|
| notices for the base model, image model, VAE, NVIDIA dependency, and any
|
| training datasets before a public release.
|
|
|
