Visual Question Answering
Transformers
Safetensors
English
Chinese
designer-instruct
image-text-to-text
vision
multimodal
Mixture of Experts
design
zen
zenlm
hanzo
Instructions to use zenlm/zen-designer-235b-a22b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zenlm/zen-designer-235b-a22b-instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="zenlm/zen-designer-235b-a22b-instruct")# Load model directly from transformers import AutoModelForMultimodalLM model = AutoModelForMultimodalLM.from_pretrained("zenlm/zen-designer-235b-a22b-instruct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc4256fd699abed7a393345458096b7e60170307490e5e939e780daa4dd1cb86
- Size of remote file:
- 4.98 GB
- SHA256:
- d3bc9997cee98c3eb337465f7c00c743cf6fe88ac8fe61d1436f5d99a0f70d16
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.