Instructions to use HaochenWang/GAR-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HaochenWang/GAR-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="HaochenWang/GAR-8B", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HaochenWang/GAR-8B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb5aa3b6024a846fdba024ee86ea0ef71c67953813658be5a5ccbd607cd68879
- Size of remote file:
- 17.2 MB
- SHA256:
- a5531cfd169b9f439ecb1339ada499771bf9a7391217dfbb51fd3a03a9fa0ce0
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