Text-to-Image
Transformers
PyTorch
English
multi-model-orchestrator
ai
machine-learning
multimodal
image-captioning
orchestration
Instructions to use kunaliitkgp09/multi-model-orchestrator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kunaliitkgp09/multi-model-orchestrator with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kunaliitkgp09/multi-model-orchestrator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download multi_model_env/bin/diffusers-cli from kunaliitkgp09/multi-model-orchestrator: direct link, hf CLI and curl.
- Browser
- Download file 273 Bytes
-
https://huggingface.co/kunaliitkgp09/multi-model-orchestrator/resolve/main/multi_model_env/bin/diffusers-cli
- Command line
-
hf download hf://kunaliitkgp09/multi-model-orchestrator/multi_model_env/bin/diffusers-cli
-
curl -L -o diffusers-cli https://huggingface.co/kunaliitkgp09/multi-model-orchestrator/resolve/main/multi_model_env/bin/diffusers-cli
273 Bytes
| #!/Users/kunaldhanda/DeepSeek/multi_model_env/bin/python3.13 | |
| # -*- coding: utf-8 -*- | |
| import re | |
| import sys | |
| from diffusers.commands.diffusers_cli import main | |
| if __name__ == '__main__': | |
| sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0]) | |
| sys.exit(main()) | |