Image Feature Extraction
Transformers
Safetensors
English
keural_vision
vision
vision-encoder
image-text
contrastive-learning
custom-architecture
vlm
Instructions to use mkd-dev/keural-vision-encoder-poc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mkd-dev/keural-vision-encoder-poc 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-poc")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mkd-dev/keural-vision-encoder-poc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_state.pt from mkd-dev/keural-vision-encoder-poc: direct link, hf CLI and curl.
- Browser
- Download file 199 MB
-
https://huggingface.co/mkd-dev/keural-vision-encoder-poc/resolve/main/training_state.pt
- Command line
-
hf download hf://mkd-dev/keural-vision-encoder-poc/training_state.pt
-
curl -L -o training_state.pt https://huggingface.co/mkd-dev/keural-vision-encoder-poc/resolve/main/training_state.pt
199 MB
- Xet hash:
- e6ee3ab7a10df680ed48d13caf0ea648bc4b2bd06d738fca8e0d65a40c790b49
- Size of remote file:
- 199 MB
- SHA256:
- 1dfb625a59763051f3f84e92da3f087dbcb359847ae12a04190279c9ad4053ac
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