Instructions to use Prem11100/Clustering-embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prem11100/Clustering-embeddings with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="Prem11100/Clustering-embeddings", device_map="auto")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("Prem11100/Clustering-embeddings") model = AutoModel.from_pretrained("Prem11100/Clustering-embeddings", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:aa3dfa0c268c47ad3dc460ec6b8b90a302af0baaeb9c8782514b2687beaaea59
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size 343216880
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