Instructions to use timm/convnext_base.clip_laion2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/convnext_base.clip_laion2b with timm:
import timm model = timm.create_model("hf_hub:timm/convnext_base.clip_laion2b", pretrained=True) - Transformers
How to use timm/convnext_base.clip_laion2b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/convnext_base.clip_laion2b")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/convnext_base.clip_laion2b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model card for convnext_base.clip_laion2b
timm CLIP (image encoder only) weights from https://huggingface.co/laion/CLIP-convnext_base_w-laion2B-s13B-b82K
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