mirror of
https://github.com/huggingface/candle.git
synced 2025-06-15 10:26:33 +00:00
ca7cf5cb3b
* Add stable diffusion 3 example Add get_qkv_linear to handle different dimensionality in linears Add stable diffusion 3 example Add use_quant_conv and use_post_quant_conv for vae in stable diffusion adapt existing AutoEncoderKLConfig to the change add forward_until_encoder_layer to ClipTextTransformer rename sd3 config to sd3_medium in mmdit; minor clean-up Enable flash-attn for mmdit impl when the feature is enabled. Add sd3 example codebase add document crediting references pass the cargo fmt test pass the clippy test * fix typos * expose cfg_scale and time_shift as options * Replace the sample image with JPG version. Change image output format accordingly. * make meaningful error messages * remove the tail-end assignment in sd3_vae_vb_rename * remove the CUDA requirement * use default_value in clap args * add use_flash_attn to turn on/off flash-attn for MMDiT at runtime * resolve clippy errors and warnings * use default_value_t * Pin the web-sys dependency. * Clippy fix. --------- Co-authored-by: Laurent <laurent.mazare@gmail.com>
Running Yolo Examples
Here, we provide two examples of how to run YOLOv8 using a Candle-compiled WASM binary and runtimes.
Pure Rust UI
To build and test the UI made in Rust you will need Trunk
From the candle-wasm-examples/yolo directory run:
Download assets:
wget -c https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/candle/examples/bike.jpeg
wget -c https://huggingface.co/lmz/candle-yolo-v8/resolve/main/yolov8s.safetensors
Run hot reload server:
trunk serve --release --public-url / --port 8080
Vanilla JS and WebWorkers
To build and test the UI made in Vanilla JS and WebWorkers, first we need to build the WASM library:
sh build-lib.sh
This will bundle the library under ./build and we can import it inside our WebWorker like a normal JS module:
import init, { Model, ModelPose } from "./build/m.js";
The full example can be found under ./lib-example.html. All needed assets are fetched from the web, so no need to download anything.
Finally, you can preview the example by running a local HTTP server. For example:
python -m http.server
Then open http://localhost:8000/lib-example.html in your browser.