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
multi-model-orchestrator / multi_model_env /lib /python3.13 /site-packages /setuptools /script (dev).tmpl
Download multi_model_env/lib/python3.13/site-packages/setuptools/script (dev).tmpl from kunaliitkgp09/multi-model-orchestrator: direct link, hf CLI and curl.
- Browser
- Download file 218 Bytes
-
https://huggingface.co/kunaliitkgp09/multi-model-orchestrator/resolve/main/multi_model_env/lib/python3.13/site-packages/setuptools/script%20(dev).tmpl
- Command line
-
hf download 'hf://kunaliitkgp09/multi-model-orchestrator/multi_model_env/lib/python3.13/site-packages/setuptools/script (dev).tmpl'
-
curl -L -o 'script (dev).tmpl' 'https://huggingface.co/kunaliitkgp09/multi-model-orchestrator/resolve/main/multi_model_env/lib/python3.13/site-packages/setuptools/script%20(dev).tmpl'
218 Bytes
| # EASY-INSTALL-DEV-SCRIPT: %(spec)r,%(script_name)r | |
| __requires__ = %(spec)r | |
| __import__('pkg_resources').require(%(spec)r) | |
| __file__ = %(dev_path)r | |
| with open(__file__) as f: | |
| exec(compile(f.read(), __file__, 'exec')) | |