Instructions to use Gaston895/aegis001 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gaston895/aegis001 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Gaston895/aegis001")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Gaston895/aegis001") model = AutoModelForCausalLM.from_pretrained("Gaston895/aegis001") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0da9dc585b1d3243c5ce7fd3c3dd50dbccac8645e9a5d1dce25f80ea10e5913
- Size of remote file:
- 121 MB
- SHA256:
- 11245487e4588b0f4128d6b4c82035212bad42ffb26f36e059e9c7f861c1f8c4
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