Image Feature Extraction
Transformers
Safetensors
English
keural_vision
vision
vision-encoder
image-text
contrastive-learning
knowledge-distillation
adaptive-tokenization
Eval Results (legacy)
Instructions to use mkd-dev/keural-vision-encoder-mid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mkd-dev/keural-vision-encoder-mid with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="mkd-dev/keural-vision-encoder-mid")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mkd-dev/keural-vision-encoder-mid", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download saliency_evolution_9ckpt.png from mkd-dev/keural-vision-encoder-mid: direct link, hf CLI and curl.
- Browser
- Download file 2.22 MB
-
https://huggingface.co/mkd-dev/keural-vision-encoder-mid/resolve/main/saliency_evolution_9ckpt.png
- Command line
-
hf download hf://mkd-dev/keural-vision-encoder-mid/saliency_evolution_9ckpt.png
-
curl -L -o saliency_evolution_9ckpt.png https://huggingface.co/mkd-dev/keural-vision-encoder-mid/resolve/main/saliency_evolution_9ckpt.png
2.22 MB

- Xet hash:
- dfc553f3e11a69564ab58344687270d4f2ad859a956323ef12778a6d436dc024
- Size of remote file:
- 2.22 MB
- SHA256:
- dc6b4b2807ed6798b8d30deb169d21f11a49fdee69dd7529398e15f6a0ae54fb
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