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Aug 5, 2026
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CIVITAI VERSION UPDATE — AnimaForge v2.11.0 (runs that start, model files that check out)
HOW TO USE: Civitai → your AnimaForge model → Add Version.
• Version name: v2.11.0
• File: marketing/Zip file 2026-08-04/AnimaForge.zip (built from
public main, app version 2.11.0 — replace the old zip)
• Paste ONLY the short blurb below as the version description.
• Also swap the "What's new" section of the model description and add the
v2.11.0 row to the version-history code block.
v2.10.0 and v2.11.0 shipped the same day and v2.10.0 was never uploaded, so
this covers both — one zip, one version entry.
Worth an actual re-upload: it fixes the bug behind the "training goes straight
to Stopped" / "auto-detect only finds the VAE" reports in the model comments.
-->
## v2.11.0 — runs that start, model files that check out
- **Training no longer dies at exit code 1 before the first step.** If any tool on your PC ever ran `accelerate config` (most Kohya guides tell you to), the config it left behind could send AnimaForge through PyTorch's multi-GPU launcher — which fails outright on Windows PyTorch builds without libuv, no matter what AnimaForge set. Runs are now pinned to the single-process launcher they always intended to use.
- **Auto-detect now finds all three files, wherever they live.** It used to look only in Forge/A1111's folders (`text_encoder/`, `VAE/`, `Stable-diffusion/`) under their exact original names — so the official Hugging Face download, which ships in ComfyUI's layout, matched the VAE and nothing else. Detection now reads each file's contents, so folder names and renames no longer matter.
- **A wrong model file is caught before Start, not 90 seconds into a dead run.** Setting a path that isn't what it claims used to sail through and die inside the trainer at exit code 1 — showing up as "Preparing" flipping straight to "Stopped". You now get a plain-English message naming the file and what it actually is.
- **ComfyUI-wrapped Anima checkpoints are called out by name.** Plenty of Anima merges are saved with `model.diffusion_model.…` weights; this trainer needs the `net.…` layout. That mismatch is now explained instead of crashing.
- **Every training run writes `logs/training.log`.** The full run log lands on disk automatically, and a failed run tells you the path — so a bug report can just attach the file.
- **Setup instructions now give the real paths and sizes** for the three files under `split_files/`.
Full detail: **github.com/SillySilk/AnimaForge**
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AnimaForge
Free, local, one-click LoRA trainer built only for Anima. Point it at a folder. Name it. Forge.
Training a LoRA shouldn't mean an evening lost in Kohya's wall of knobs. AnimaForge is a free Windows app that does the whole run from one screen: pick your image folder, name the LoRA, hit Train. It auto-captions (WD14 tags + JoyCaption descriptions), calculates sane step counts for your dataset size, and trains with settings hand-tuned for one model — Anima. That focus is the whole point.
You watch it learn. Preview images render every epoch while training runs. Flip on Compare epochs to see them side by side, spot the earliest epoch that already nails your character, and stop right there — no over-training guesswork, no re-runs. Stopped too soon or crashed? Resume from the last checkpoint.
It has opinions, so you don't need any. Pick a preset — Person, Object / Concept, or Style — and the subject handling, optimizer, network size, and step budget are set. Power users can save their own presets, switch optimizers (Prodigy auto-LR or classic AdamW8bit), and preview the exact training config before launch. Guard rails catch the classics before they burn a run: empty captions (one-click fix), low VRAM, even duplicate images hiding in your dataset.
It finishes the job. One click copies the trained LoRA into your Forge or ComfyUI models folder — with the trigger word baked into the filename, so anyone you share it with knows exactly what to type. A batch queue captions and trains multiple LoRAs unattended, and survives a restart.
Runs on your machine. Your images, captions, and LoRAs never leave your computer. No subscriptions, no queues, no uploads.
WHAT'S NEW — v2.9.3
• Stray USE_LIBUV in your own Windows environment? Fix it without leaving AnimaForge — Setup → Training Environment adds a checkbox that forces AnimaForge's setting even when your environment already has one, plus a button that clears it from Windows outright. No more manual System Properties surgery
• See exactly what's in play — a live status line in Setup shows the effective USE_LIBUV and where it's coming from, so you're never guessing whether the fix applies to you
• Reset Training Environment — one click re-verifies PyTorch from scratch when something about your setup looks stale, without losing your last known-good result unless the fresh check genuinely can't confirm it
• Clear now tells you whether it worked — success or failure is logged right there instead of the button just going grey
Full history: github.com/SillySilk/AnimaForge
WHAT YOU'LL NEED
• Windows + NVIDIA GPU (CUDA) — includes RTX 50-series. No CPU/AMD path.
• ~16 GB VRAM comfortable; low-VRAM mode reaches smaller cards (8 GB practical floor).
• The three Anima files (Setup auto-detects them): DiT checkpoint, Qwen3 text encoder, Qwen-Image VAE — from Hugging Face circlestone-labs/Anima.
GET IT → github.com/SillySilk/AnimaForge
install.bat (one-time — builds a self-contained .venv with the full stack), then launch.bat.
100% free and open source (MIT). Built for the Anima community. Forge something great.
------------------------------ ② VERSION DESCRIPTION (v2.9.3) — see changelog-2026-08-03.md ------------------------------
v2.9.3 — self-service fixes for the training crash
• Stray USE_LIBUV in your own Windows environment? Fix it without leaving AnimaForge — Setup → Training Environment adds a checkbox that forces AnimaForge's setting even when your environment already has one, plus a button that clears it from Windows outright. No more manual System Properties surgery.
• See exactly what's in play — a live status line in Setup shows the effective USE_LIBUV and where it's coming from, so you're never guessing whether the fix applies to you.
• Reset Training Environment — one click re-verifies PyTorch from scratch when something about your setup looks stale, without losing your last known-good result unless the fresh check genuinely can't confirm it.
• Clear now tells you whether it worked — success or failure is logged right there instead of the button just going grey.
Full detail: github.com/SillySilk/AnimaForge
------------------------------ ③ VERSION HISTORY (bottom of description) ------------------------------
(Insert a CODE BLOCK via the </> toolbar button, then paste the table so the columns hold.
If you'd rather not use a code block, use Variant B in version-history.md instead.)
VERSION DATE WHAT CHANGED
------- ---------- ------------------------------------------------------------
v2.7 2026-07-10 LM Studio removed entirely — captioning is fully local (WD14
+ JoyCaption, merged mechanically), no external LLM server
needed or contacted · fixes the bug where some .nl captions
randomly came out as raw tags instead of prose · Combine now
de-dupes and tidies booru tags with no model in the loop ·
Describe gains "Redo all" — re-caption everything with a
live per-image stream · steadier shutdown
v2.6 2026-07-10 Optional "check for updates at startup" (Setup) notifies you
when a newer build has landed · the check runs safely off the
UI thread · icon/caption fixes
v2.5 2026-07-09 Captioning never overwrites existing caption files without
asking (keep / overwrite / set it once) · caption runs resume
where they stopped, and a killed training run comes back even
if you moved its folder · the batch queue captions each set
then trains it, settling every conflict up front · Add to
Batch is back on the front page; Restart from Top re-runs a
finished queue · find/replace rules fix misgendering and ban
tags · re-running Auto-Tag no longer duplicates every tag
v2.3 2026-07-06 Fixes a "division by zero" crash when aspect-ratio bucketing
met an image with a side under 64 px (it killed the run at
exit code 1) — now caught before launch with a one-click fix,
and auto-handled on unattended/batch runs · corrected
epoch/preview step math · live sample-preview UI overhaul
v2.2 2026-07-04 Pick your own UI font (Setup → App Defaults): forge faces,
system font, or any installed font · fixes non-Latin
readability (CJK, Cyrillic) · applies live, no restart ·
default look unchanged
v2.1 2026-07-03 Project autosave under the LoRA name at both caption
milestones · Restore captions from Saved Sets · low-VRAM
warning auto-continues after 10 s on unattended runs ·
in-app updater (Updates on the front page)
v2.0 2026-07-02 New brand badge across the app · preset picker shows each
intent's step math · one launch point (Options configures,
the front launches) · config preview beside Start ·
monospace version digits · spacing polish
v1.9 2026-07-02 Training presets (Person/Object/Style + save your own) ·
compare epochs side-by-side · Deliver to ComfyUI · trigger
word in the delivered filename · duplicate-image catcher ·
readable UI text (CJK-friendly) · accurate speed/ETA dials ·
previews every epoch · side-by-side installs stay separate
v1.1 2026-07-01 The forge redesign: everything runs from one screen, with
analog Epoch/Loss/Speed/ETA dials · optimizer presets
(Prodigy / AdamW8bit) · RTX 50-series support · empty-caption
guard with one-click fix · config preview · per-epoch
preview schedule on the progress bar
v1.0 2026-06-30 Launch: one-click caption→train for Anima (WD14 + JoyCaption)
· auto step counts tuned to dataset size · batch queue that
survives restarts · crash recovery + resume · low-VRAM mode
· Name Cast for consistent character triggers

