Instructions to use ArtusDev/Delta-Vector_Austral-24B-Winton-EXL2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArtusDev/Delta-Vector_Austral-24B-Winton-EXL2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ArtusDev/Delta-Vector_Austral-24B-Winton-EXL2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
EXL2 Quants of Delta-Vector/Austral-24B-Winton
EXL2 quants of Delta-Vector/Austral-24B-Winton using exllamav2 for quantization.
Quants
Downloading quants with huggingface-cli
Click to view download instructions
Install hugginface-cli:
pip install -U "huggingface_hub[cli]"
Download quant by targeting the specific quant revision (branch):
huggingface-cli download ArtusDev/Delta-Vector_Austral-24B-Winton-EXL2 --revision "5.0bpw_H6" --local-dir ./
Inference Providers NEW
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Model tree for ArtusDev/Delta-Vector_Austral-24B-Winton-EXL2
Base model
mistralai/Mistral-Small-3.1-24B-Base-2503 Finetuned
LatitudeGames/Harbinger-24B Finetuned
Delta-Vector/Austral-24B-Base Finetuned
Delta-Vector/Austral-SFT-KTO Finetuned
Delta-Vector/Austral-24B-Winton