Revert "Add CLIP to KerasCV (#2331)"

This reverts commit 15db57c.

Author: divyashreepathihalli

.github/workflows/actions.yml

@@ -38,8 +38,6 @@ jobs:
         pip install torch>=2.0.1+cpu
         pip install "jax[cpu]"
         pip install keras-core
-        pip install keras-nlp-nightly --no-deps
-        pip install tensorflow-text==2.15
         pip install -e ".[tests]" --progress-bar off --upgrade
     - name: Test with pytest
       env:
@@ -77,7 +75,6 @@ jobs:
       run: |
         pip install -r requirements.txt
         pip install -e ".[tests]" --progress-bar off --upgrade
-        pip install keras-nlp-nightly
     - name: Test with pytest
       env:
         TEST_CUSTOM_OPS: false # TODO(ianstenbit): test custom ops, or figure out what our story is here

.kokoro/github/ubuntu/gpu/build.sh

@@ -29,26 +29,21 @@ then
    pip install --extra-index-url https://download.pytorch.org/whl/cpu torch==2.1.0+cpu
    pip install torchvision~=0.16.0
    pip install "jax[cpu]"
-   pip install keras-nlp-nightly --no-deps
-   pip install tensorflow-text==2.15
 
 elif [ "$KERAS_BACKEND" == "tensorflow" ]
 then
    echo "TensorFlow backend detected."
    pip install -r requirements-tensorflow-cuda.txt --progress-bar off
-   pip install keras-nlp-nightly
 
 elif [ "$KERAS_BACKEND" == "jax" ]
 then
    echo "JAX backend detected."
    pip install -r requirements-jax-cuda.txt --progress-bar off
-   pip install keras-nlp-nightly
 
 elif [ "$KERAS_BACKEND" == "torch" ]
 then
    echo "PyTorch backend detected."
    pip install -r requirements-torch-cuda.txt --progress-bar off
-   pip install keras-nlp-nightly
 fi
 
 pip install --no-deps -e "." --progress-bar off

keras_cv/models/__init__.py

@@ -183,7 +183,6 @@
 from keras_cv.models.backbones.vit_det.vit_det_aliases import ViTDetLBackbone
 from keras_cv.models.backbones.vit_det.vit_det_backbone import ViTDetBackbone
 from keras_cv.models.classification.image_classifier import ImageClassifier
-from keras_cv.models.feature_extractor.clip import CLIP
 from keras_cv.models.object_detection.retinanet.retinanet import RetinaNet
 from keras_cv.models.object_detection.yolo_v8.yolo_v8_backbone import (
     YOLOV8Backbone,