Instructions to use bilbo991/clip-mixer-300k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bilbo991/clip-mixer-300k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bilbo991/clip-mixer-300k")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("bilbo991/clip-mixer-300k") model = AutoModel.from_pretrained("bilbo991/clip-mixer-300k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
clip-mixer-300k / runs /Aug16_14-43-59_cvrl-flynn-ws2 /events.out.tfevents.1692211514.cvrl-flynn-ws2.10527.0
- Xet hash:
- 6ed53cb37cd5ec38ea76612868bea3f9406a5297c21eff3f1edc91ef90184d29
- Size of remote file:
- 11.2 kB
- SHA256:
- c2d8a5a443139a0564febb115915dd72f72b046c5f9106b1c0d6e9b3e5261c6f
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