LTXAVTEModel.load_sd passes the full checkpoint sd to Gemma3_12B.load_state_dict,
which has vision_model and multi_modal_projector as real attributes with matching
key names. Vision weights are already present after DualCLIPLoader runs.
Drop _vision_loaded flag check; detect vision capability by attribute existence.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Checkpoints converted for ComfyUI use vision_model.* and
multi_modal_projector.* as top-level keys directly, not the HuggingFace
model.vision_tower.* nesting. Accept both formats.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
When no vision keys are found, log the top-level key prefixes actually
present in the checkpoint so the user can see whether the vision tower
was stripped. Also rename all [FunPackGemmaLoader] log prefixes to
[FunPackGemmaVision].
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Companion to DualCLIPLoader: takes the already-built CLIP object (which has
the correct LTXAVTEModel structure) and loads the SigLIP vision tower +
multi-modal projector from the Gemma3-12B-IT checkpoint, setting
_vision_loaded=True. Workflow: DualCLIPLoader → FunPackGemmaVision → Studio.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
FunPackGemmaLoader: drop-in replacement for Load CLIP Model that additionally
loads the SigLIP vision tower and multi-modal projector from Google's
Gemma3-12B-IT checkpoint into the already-initialized Gemma3_12B module,
enabling reference-image vision prompting without a separate CLIP Vision model.
Vision prompting: _v2_encode_prompt accepts reference_image; when the clip
has _vision_loaded=True, tokenizes with image=reference_image and
skip_template=False so Gemma3 sees the reference frame before generating
conditioning. Cache key includes image fingerprint to avoid stale hits.
source_image from Studio/refine_v2 flows through to _v2_conditioning_source.
K/V injection revamp (Technique 5): identity blocks in i2v mode now use
in-context conditioning instead of lerp injection. Pre-hook prepends reference
hidden-state tokens to vx and extends v_pe with neutral-rotation entries
(cos=1, sin=0) so video tokens self-attend to reference tokens in attn1.
Post-hook crops the reference prefix from the block output. Strength raised
from 0.02 → 1.0 (sigma-gated: active at 0.35–0.80). _extend_v_pe helper
handles 2-D/3-D/4-D PE tensors. Anchor blocks keep the existing lerp path.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Removed from LORA_BLOCK_TYPE_PROFILES, LORA_TYPE_BLOCK_ZONES,
LORA_REFINER_TYPE_PROFILES, ACTION_LORA_TYPES, the validation
special-case, and the Studio JS LORA_TYPES dropdown.
normalize_lora_type() keeps the concept->action mapping for silent
backwards compatibility with any existing saved stacks.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add LORA_TYPE_BLOCK_ZONES: type-aware block zones that suppress bad-fit
blocks to 0.0 and mildly boost good-zone blocks per LoRA type
- Add SEMANTIC_ANCHOR_BLOCKS {14, 19}: confirmed semantic focal points
(PAG default=14, STG defaults=14,19) protected from all suppression
- Add _semantic_anchor_quality: uses LoRA energy share in blocks 14+19
as a quality signal, scaling all block weights 0.92-1.08x accordingly
- Stack priority: weaker LoRA keeps base scale on anchor blocks instead
of being damped, letting the dominant signal carry semantic content
- Fix range display: status line now shows effective weights (model_weight
* scale) instead of raw multipliers; adds zeroed= and anchor_q= fields
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
