Readme gallery (#834)

* More readme tweaks.

* Update README.md
This commit is contained in:
Laurent Mazare
2023-09-13 10:05:47 +02:00
committed by GitHub
parent cbd36157ac
commit e6f040d6e3
3 changed files with 41 additions and 21 deletions

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@ -45,40 +45,48 @@ For more advanced examples, please have a look at the following section.
## Check out our examples
Check out our [examples](./candle-examples/examples/):
These online demos run entirely in your browser:
- [yolo](https://huggingface.co/spaces/lmz/candle-yolo): pose estimation and
object recognition.
- [whisper](https://huggingface.co/spaces/lmz/candle-whisper): text to speech.
- [LLaMA2](https://huggingface.co/spaces/lmz/candle-llama2): text generation.
We also provide a some command line based examples using state of the art models:
- [Whisper](./candle-examples/examples/whisper/): speech recognition model.
- [LLaMA and LLaMA-v2](./candle-examples/examples/llama/): general LLM.
- [Falcon](./candle-examples/examples/falcon/): general LLM.
- [Bert](./candle-examples/examples/bert/): useful for sentence embeddings.
- [StarCoder](./candle-examples/examples/bigcode/): LLM specialized to code
generation.
- [Stable Diffusion](./candle-examples/examples/stable-diffusion/): text to
image generative model, support for the 1.5, 2.1, and SDXL 1.0 versions.
- [DINOv2](./candle-examples/examples/dinov2/): computer vision model trained
using self-supervision (can be used for imagenet classification, depth
evaluation, segmentation).
- [Quantized LLaMA](./candle-examples/examples/quantized/): quantized version of
the LLaMA model using the same quantization techniques as
[llama.cpp](https://github.com/ggerganov/llama.cpp).
<img src="https://github.com/huggingface/candle/raw/main/candle-examples/examples/quantized/assets/aoc.gif" width="600">
- [Stable Diffusion](./candle-examples/examples/stable-diffusion/): text to
image generative model, support for the 1.5, 2.1, and SDXL 1.0 versions.
<img src="https://github.com/huggingface/candle/raw/main/candle-examples/examples/stable-diffusion/assets/stable-diffusion-xl.jpg" width="200">
- [yolo-v3](./candle-examples/examples/yolo-v3/) and
[yolo-v8](./candle-examples/examples/yolo-v8/): object detection and pose
estimation models.
<img src="https://github.com/huggingface/candle/raw/main/candle-examples/examples/yolo-v8/assets/bike.od.jpg" width="200"><img src="https://github.com/huggingface/candle/raw/main/candle-examples/examples/yolo-v8/assets/bike.pose.jpg" width="200">
- [segment-anything](./candle-examples/examples/segment-anything/): image
segmentation model with prompt.
Run them using the following commands:
<img src="https://github.com/huggingface/candle/raw/main/candle-examples/examples/segment-anything/assets/sam_merged.jpg" width="200">
- [Whisper](./candle-examples/examples/whisper/): speech recognition model.
- [Bert](./candle-examples/examples/bert/): useful for sentence embeddings.
- [DINOv2](./candle-examples/examples/dinov2/): computer vision model trained
using self-supervision (can be used for imagenet classification, depth
evaluation, segmentation).
Run them using commands like:
```
cargo run --example whisper --release
cargo run --example llama --release
cargo run --example falcon --release
cargo run --example bert --release
cargo run --example bigcode --release
cargo run --example stable-diffusion --release -- --prompt "a rusty robot holding a fire torch"
cargo run --example dinov2 --release -- --image path/to/myinput.jpg
cargo run --example quantized --release
cargo run --example yolo-v3 --release -- myimage.jpg
cargo run --example yolo-v8 --release -- myimage.jpg # for pose estimation, add --task pose
cargo run --example segment-anything --release -- --image myimage.jpg
```
In order to use **CUDA** add `--features cuda` to the example command line. If

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@ -1,7 +1,19 @@
# candle-starcoder: code generation model
StarCoder/BigCode is a LLM model specialized to code generation.
[StarCoder/BigCode](https://huggingface.co/bigcode/starcoderbase-1b) is a LLM
model specialized to code generation. The initial model was trained on 80
programming languages.
## Running some example
```bash
cargo run --example bigcode --release -- --prompt "fn fact(n: u64) -> u64 "
> fn fact(n: u64) -> u64 {
> if n == 0 {
> 1
> } else {
> n * fact(n - 1)
> }
> }
```

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@ -13,7 +13,7 @@ Space](https://huggingface.co/spaces/lmz/candle-yolo). The model then fully runs
in your browser using WebAssembly - if you use a custom image it will never
leave your phone/computer!
## Running some example.
## Running some example
### Object Detection
```bash