Merge branch 'master' into fix/gpu-memory-failure-handling

docs/backend.md

@@ -193,8 +193,9 @@ weights, compute buffers and caches must
 still fit the runner's capacity checks. Offloading weights does not guarantee
 that every resolution or frame count will fit, and auto-fit does not change a
 component to CPU computation solely because its full weights exceed VRAM.
-If a VAE decode fails, auto-fit retries with spatial tiling; supported video
-decoders try temporal tiling first and can then add spatial tiling.
+If a VAE decode fails, decoding retries with spatial tiling even when `--auto-fit`
+is off; supported video decoders try temporal tiling first and can then add
+spatial tiling. Spatial retries use half-size tiles along each latent dimension.
 
 ## Modules
 

docs/sensenova_u1.md

@@ -0,0 +1,46 @@
+# How to Use
+
+SenseNova U1.5 is an 8B MoT model that performs diffusion directly in RGB pixel
+space. It does not require a separate text encoder or VAE.
+
+## Download weights
+
+- Download SenseNova U1.5 8B MoT
+    - safetensors: https://huggingface.co/sensenova/SenseNova-U1.5-8B-MoT
+
+Pass the complete downloaded repository directory to `--model`. The directory
+must contain `model.safetensors.index.json`, every referenced Safetensors shard,
+and the tokenizer files.
+
+## Examples
+
+### CUDA
+
+```bash
+./bin/sd-cli \
+  --model /path/to/SenseNova-U1.5-8B-MoT \
+  --prompt "a red cube on a white background" \
+  --width 2048 \
+  --height 2048 \
+  --steps 50 \
+  --cfg-scale 4 \
+  --flow-shift 3 \
+  --seed 42 \
+  --sampling-method euler \
+  --rng cuda \
+  --fa \
+  --output output.png
+```
+
+## Notes
+
+- To match the official non-thinking text-to-image pipeline, use 50 Euler
+  steps, CFG 4, flow shift 3, seed 42, CUDA RNG, and an empty negative prompt.
+- Width and height must be multiples of 32. The trained 1:1 resolution is
+  2048x2048; lower resolutions are useful for smoke tests but are outside the
+  training buckets.
+- The SenseNova prompt template and unconditional prompt are built
+  automatically.
+- This implementation supports non-thinking text-to-image generation. Image
+  editing, visual understanding, interleaved generation, and thinking-mode
+  prompt expansion are not implemented.

docs/troubleshooting.md

@@ -0,0 +1,45 @@
+# Troubleshooting
+
+## Completely black or white images or videos / NaNs
+
+Some ggml backends can encounter numerical overflow during inference, producing
+NaN (not-a-number) values. This can result in completely black or white images or videos.
+Whether it happens can depend on the backend, device, model, and weight format.
+
+Known overflow issues have been addressed as far as possible, but the maintainer
+has limited hardware and cannot test every combination. Some cases may therefore
+still need a manual workaround.
+
+These options are supported by both `sd-cli` and `sd-server`. If you encounter
+this problem, add them to your CLI generation command or server startup command:
+
+```sh
+--linear-scale 0.0078125 --attn-scale 0.0078125
+```
+
+For `sd-server`, restart the server after changing these startup options. Run the
+same prompt and seed again to see whether the output recovers. If the problem
+persists, try smaller positive values, for example:
+
+```sh
+--linear-scale 0.00390625 --attn-scale 0.00390625
+```
+
+These options reduce intermediate values and compensate afterwards to preserve
+the intended output scale:
+
+- `--linear-scale` scales Linear inputs before matrix multiplication and rescales
+  the result.
+- `--attn-scale` scales attention keys and values (K/V). It takes effect only in
+  the Flash Attention path, where `--fa` or `--diffusion-fa` is enabled and the
+  backend supports it.
+
+The two values can be set independently and apply across model components. The
+default `0` preserves each model's built-in settings; `1` explicitly disables the
+corresponding scaling. Overrides must be finite positive values. C API users can
+set `linear_scale` and `attn_scale` in `sd_ctx_params_t`.
+
+If the problem persists after trying the relevant steps above,
+[submit a bug report](https://github.com/leejet/stable-diffusion.cpp/issues/new?template=bug_report.yml).
+Include your full command, backend and hardware, model and weight format, logs,
+and the scale values you tried with their results.