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", dtype="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 6cc32504a504d2b0e9f78e45cbdf05e273d4dcd3e951f4e4e365285866fee24b
- Size of remote file:
- 47.6 kB
- SHA256:
- 040a812af83555657acca84cae39a2b64fd59a148763e319c650d93bb727bd5c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.