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Use the hub model file when possible. (#1190)
* Use the hub model file when possible. * And add a mention in the main readme.
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@ -56,7 +56,7 @@ These online demos run entirely in your browser:
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- [T5](https://huggingface.co/spaces/radames/Candle-T5-Generation-Wasm): text generation.
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- [Phi-v1.5](https://huggingface.co/spaces/radames/Candle-Phi-1.5-Wasm): text generation.
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- [Segment Anything Model](https://huggingface.co/spaces/radames/candle-segment-anything-wasm): Image segmentation.
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- [Blip](https://huggingface.co/spaces/radames/Candle-BLIP-Image-Captioning): image captioning.
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- [BLIP](https://huggingface.co/spaces/radames/Candle-BLIP-Image-Captioning): image captioning.
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We also provide a some command line based examples using state of the art models:
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@ -96,7 +96,8 @@ We also provide a some command line based examples using state of the art models
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<img src="https://github.com/huggingface/candle/raw/main/candle-examples/examples/segment-anything/assets/sam_merged.jpg" width="200">
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- [Whisper](./candle-examples/examples/whisper/): speech recognition model.
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- [T5](./candle-examples/examples/t5), [Bert](./candle-examples/examples/bert/): useful for sentence embeddings.
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- [T5](./candle-examples/examples/t5), [Bert](./candle-examples/examples/bert/),
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[JinaBert](./candle-examples/examples/jina-bert/) : useful for sentence embeddings.
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- [DINOv2](./candle-examples/examples/dinov2/): computer vision model trained
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using self-supervision (can be used for imagenet classification, depth
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evaluation, segmentation).
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