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
File size: 904 Bytes
b4740c6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | import sys
from .compat import chardet
# This code exists for backwards compatibility reasons.
# I don't like it either. Just look the other way. :)
for package in ("urllib3", "idna"):
locals()[package] = __import__(package)
# This traversal is apparently necessary such that the identities are
# preserved (requests.packages.urllib3.* is urllib3.*)
for mod in list(sys.modules):
if mod == package or mod.startswith(f"{package}."):
sys.modules[f"requests.packages.{mod}"] = sys.modules[mod]
if chardet is not None:
target = chardet.__name__
for mod in list(sys.modules):
if mod == target or mod.startswith(f"{target}."):
imported_mod = sys.modules[mod]
sys.modules[f"requests.packages.{mod}"] = imported_mod
mod = mod.replace(target, "chardet")
sys.modules[f"requests.packages.{mod}"] = imported_mod
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