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")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenDILabCommunity/HUMOR-RM-Keye-VL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from OpenDILabCommunity/HUMOR-RM-Keye-VL: direct link, hf CLI and curl.
- Browser
- Download file 115 Bytes
-
https://huggingface.co/OpenDILabCommunity/HUMOR-RM-Keye-VL/resolve/main/processor_config.json
- Command line
-
hf download hf://OpenDILabCommunity/HUMOR-RM-Keye-VL/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/OpenDILabCommunity/HUMOR-RM-Keye-VL/resolve/main/processor_config.json
115 Bytes
- Xet hash:
- 9e0fd588d963f5485de6fde198e78be4b576d778a19384b3e1db62eabf0230f9
- Size of remote file:
- 115 Bytes
- SHA256:
- 4ebdfbb344ade75d6cfc4c1ba0019562ae99cb0c3f378fd41026dcf839c3fe3b
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