Image Classification
Transformers
Safetensors
English
Chinese
vision
reward-model
reinforcement-learning
multimodal
llama-factory
Instructions to use OpenDILabCommunity/HUMOR-RM-Keye-VL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenDILabCommunity/HUMOR-RM-Keye-VL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="OpenDILabCommunity/HUMOR-RM-Keye-VL") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenDILabCommunity/HUMOR-RM-Keye-VL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de7f05f65b8fa2f8d589064719c0fb8513d240dd2138978a828b0a2d48f76ded
- Size of remote file:
- 2.78 MB
- SHA256:
- ca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.