Instructions to use zeromodels/clip_vit_large_14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use zeromodels/clip_vit_large_14 with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Keras
How to use zeromodels/clip_vit_large_14 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://zeromodels/clip_vit_large_14") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- README.md +19 -0
- model.weights.h5 +3 -0
- tokenizer.json +0 -0
README.md
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---
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pipeline_tag: zero-shot-image-classification
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license: mit
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library_name: kerasformers
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tags:
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- keras
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- kerasformers
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- clip
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---
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# clip_vit_large_14 (Keras 3)
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Pure-Keras 3 weights for [kerasformers](https://github.com/IMvision12/KerasFormers), mirrored from the GitHub release. License: `mit`.
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```python
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from kerasformers.models.clip import CLIPModel, CLIPTokenizer
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model = CLIPModel.from_weights("clip_vit_large_14")
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tokenizer = CLIPTokenizer.from_weights("clip_vit_large_14")
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```
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model.weights.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:aac08e2bb636a271c18f644b866e7674e5e47fc7e0d3498a4e9dd8f3c17d7b7a
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size 1711603400
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tokenizer.json
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