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/lib/python3.13/site-packages/PIL/ImagePath.py from kunaliitkgp09/multi-model-orchestrator: direct link, hf CLI and curl.
- Browser
- Download file 371 Bytes
-
https://huggingface.co/kunaliitkgp09/multi-model-orchestrator/resolve/main/multi_model_env/lib/python3.13/site-packages/PIL/ImagePath.py
- Command line
-
hf download hf://kunaliitkgp09/multi-model-orchestrator/multi_model_env/lib/python3.13/site-packages/PIL/ImagePath.py
-
curl -L -o ImagePath.py https://huggingface.co/kunaliitkgp09/multi-model-orchestrator/resolve/main/multi_model_env/lib/python3.13/site-packages/PIL/ImagePath.py
371 Bytes
| # | |
| # The Python Imaging Library | |
| # $Id$ | |
| # | |
| # path interface | |
| # | |
| # History: | |
| # 1996-11-04 fl Created | |
| # 2002-04-14 fl Added documentation stub class | |
| # | |
| # Copyright (c) Secret Labs AB 1997. | |
| # Copyright (c) Fredrik Lundh 1996. | |
| # | |
| # See the README file for information on usage and redistribution. | |
| # | |
| from __future__ import annotations | |
| from . import Image | |
| Path = Image.core.path | |