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/idna/compat.py from kunaliitkgp09/multi-model-orchestrator: direct link, hf CLI and curl.
- Browser
- Download file 316 Bytes
-
https://huggingface.co/kunaliitkgp09/multi-model-orchestrator/resolve/main/multi_model_env/lib/python3.13/site-packages/idna/compat.py
- Command line
-
hf download hf://kunaliitkgp09/multi-model-orchestrator/multi_model_env/lib/python3.13/site-packages/idna/compat.py
-
curl -L -o compat.py https://huggingface.co/kunaliitkgp09/multi-model-orchestrator/resolve/main/multi_model_env/lib/python3.13/site-packages/idna/compat.py
316 Bytes
| from typing import Any, Union | |
| from .core import decode, encode | |
| def ToASCII(label: str) -> bytes: | |
| return encode(label) | |
| def ToUnicode(label: Union[bytes, bytearray]) -> str: | |
| return decode(label) | |
| def nameprep(s: Any) -> None: | |
| raise NotImplementedError("IDNA 2008 does not utilise nameprep protocol") | |