Feature Extraction
Transformers
Safetensors
the_net_omni
custom_code
multimodal
mixture-of-experts
weight-sharing
8-bit precision
compressed-tensors
Instructions to use JacobLinCool/the-net with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JacobLinCool/the-net with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="JacobLinCool/the-net", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("JacobLinCool/the-net", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download __init__.py from JacobLinCool/the-net: direct link, hf CLI and curl.
- Browser
- Download file 119 Bytes
-
https://huggingface.co/JacobLinCool/the-net/resolve/main/__init__.py
- Command line
-
hf download hf://JacobLinCool/the-net/__init__.py
-
curl -L -o __init__.py https://huggingface.co/JacobLinCool/the-net/resolve/main/__init__.py
119 Bytes
| from .configuration_omni import OmniConfig | |
| from .modeling_omni import OmniModel | |
| __all__ = ["OmniConfig", "OmniModel"] | |