From 653093228566c27093163d2a0205acae8423310b Mon Sep 17 00:00:00 2001 From: Laurent Mazare Date: Sun, 3 Mar 2024 16:25:14 +0100 Subject: Add the new models to the main readme. (#1797) --- README.md | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) (limited to 'README.md') diff --git a/README.md b/README.md index 00f0b319..fd80069e 100644 --- a/README.md +++ b/README.md @@ -84,8 +84,6 @@ We also provide a some command line based examples using state of the art models - [Replit-code-v1.5](./candle-examples/examples/replit-code/): a 3.3b LLM specialized for code completion. - [Yi-6B / Yi-34B](./candle-examples/examples/yi/): two bilingual (English/Chinese) general LLMs with 6b and 34b parameters. -- [EnCodec](./candle-examples/examples/encodec/): high-quality audio compression - model using residual vector quantization. - [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). @@ -112,7 +110,12 @@ We also provide a some command line based examples using state of the art models +- [SegFormer](./candle-examples/examples/segformer/): transformer based semantic segmantation model. - [Whisper](./candle-examples/examples/whisper/): speech recognition model. +- [EnCodec](./candle-examples/examples/encodec/): high-quality audio compression + model using residual vector quantization. +- [MetaVoice](./candle-examples/examples/metavoice/): foundational model for + text-to-speech. - [T5](./candle-examples/examples/t5), [Bert](./candle-examples/examples/bert/), [JinaBert](./candle-examples/examples/jina-bert/) : useful for sentence embeddings. - [DINOv2](./candle-examples/examples/dinov2/): computer vision model trained @@ -220,13 +223,15 @@ If you have an addition to this list, please submit a pull request. - BLIP. - TrOCR. - Audio. - - Whisper, multi-lingual text-to-speech. + - Whisper, multi-lingual speech-to-text. - EnCodec, audio compression model. + - MetaVoice-1B, text-to-speech model. - Computer Vision Models. - DINOv2, ConvMixer, EfficientNet, ResNet, ViT, VGG, RepVGG, ConvNeXT, ConvNeXTv2, MobileOne, EfficientVit (MSRA). - yolo-v3, yolo-v8. - Segment-Anything Model (SAM). + - SegFormer. - File formats: load models from safetensors, npz, ggml, or PyTorch files. - Serverless (on CPU), small and fast deployments. - Quantization support using the llama.cpp quantized types. -- cgit v1.2.3