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-hika/keural-vision-encoder-mid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mkd-hika/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-hika/keural-vision-encoder-mid")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mkd-hika/keural-vision-encoder-mid", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66bbf651935a4ff3a3257549fc0b66ad08fe6b5021b272194dc6c432d5e05ff9
- Size of remote file:
- 9.05 MB
- SHA256:
- 10c8ef42816f2f2dab26de3295ef8ffb651c515feba37fde5785caabdba5d99a
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