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/requests/certs.py from kunaliitkgp09/multi-model-orchestrator: direct link, hf CLI and curl.
- Browser
- Download file 429 Bytes
-
https://huggingface.co/kunaliitkgp09/multi-model-orchestrator/resolve/main/multi_model_env/lib/python3.13/site-packages/requests/certs.py
- Command line
-
hf download hf://kunaliitkgp09/multi-model-orchestrator/multi_model_env/lib/python3.13/site-packages/requests/certs.py
-
curl -L -o certs.py https://huggingface.co/kunaliitkgp09/multi-model-orchestrator/resolve/main/multi_model_env/lib/python3.13/site-packages/requests/certs.py
429 Bytes
| #!/usr/bin/env python | |
| """ | |
| requests.certs | |
| ~~~~~~~~~~~~~~ | |
| This module returns the preferred default CA certificate bundle. There is | |
| only one — the one from the certifi package. | |
| If you are packaging Requests, e.g., for a Linux distribution or a managed | |
| environment, you can change the definition of where() to return a separately | |
| packaged CA bundle. | |
| """ | |
| from certifi import where | |
| if __name__ == "__main__": | |
| print(where()) | |