Any-to-Any
Transformers
English
Chinese
qwen2
text-generation
medical
vision-language
multimodal
unified-model
medical-vqa
text-to-image
image-to-text
medical-understanding
report-generation
interleaved-multimodal
modality-transfer
custom_code
Instructions to use General-Medical-AI/UniMedVL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use General-Medical-AI/UniMedVL with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("General-Medical-AI/UniMedVL", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("General-Medical-AI/UniMedVL", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f75bf663bf4f4a1c1fb0b58b79da088baec662fb08c71dfe2b46af4417d4b37f
- Size of remote file:
- 13.7 MB
- SHA256:
- cd1d65eeddfde3c9a9bbc59ec714c2c4fa95bf9e96f7f1817c58ca26fc3feee7
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