Reverts 6bf533e, 78c9625, 4bacc9c, 993e5e4, ae337b5 and c4d8018 —
gguf_support.py, loaders.py and their tests are byte-identical to
6f04642. Nothing else is touched.
The quantized path loaded fast and gave the sampler a model it could not
run: shape [21504, 5376] against an input of 22848x5376, one 1344-token
unit apart. Expanding at load is slow and works.
Attention and SLA are applied to a clone of a one-entry weight cache
keyed on file identity + dtypes, so a sparsity change skips the disk.
GGUF dequantization now runs across threads instead of serially.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
It is a toggle now, not a value in the list: SLA takes H3's packed self-attention
and the chosen backend takes the text refiner, masked calls and dense-last steps.
When SLA does not take, the chosen backend is still installed on its own.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Picked in the diffusion model loader's attention list, not wired as a node.
Six settings folded under Advanced; offered only where CUDA and Triton run it
and ignored on any model that is not H3. Kernel vendored from LightX2V.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Rows are picked from a searchable list of installed files instead of typed into a
table of dropdowns, and an input the node calls advanced (the trained stack) is
folded away unless something feeds it.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Empty is a working state now, logged as "No active LoRAs", so the hop every
LoRA needs is already wired into a fresh pipeline.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Quantization + a per-model attention backend read from ComfyUI's own registry, so only
installed ones are offered. The LoRA loader now takes its own list and scores wrapper
prefixes against the model's key map, instead of applying a diffusers LoRA as a silent no-op.
digital-garbage