| --- |
| license: apache-2.0 |
| library_name: mlx |
| --- |
| |
| # mlx-community/clip-vit-large-patch14 |
| This model was converted to MLX format from [`clip-vit-large-patch14`](https://huggingface.co/clip-vit-large-patch14). |
| Refer to the [original model card](https://huggingface.co/openai/clip-vit-large-patch14) for more details on the model. |
| ## Use with mlx-examples |
|
|
| Download the repository 👇 |
|
|
| ``` |
| pip install huggingface_hub hf_transfer |
| |
| export HF_HUB_ENABLE_HF_TRANSFER=1 |
| huggingface-cli download --local-dir <LOCAL FOLDER PATH> mlx-community/clip-vit-large-patch14 |
| ``` |
|
|
| Install `mlx-examples`. |
|
|
| ```bash |
| git clone git@github.com:ml-explore/mlx-examples.git |
| cd clip |
| pip install -r requirements.txt |
| ``` |
|
|
| Run the model. |
|
|
| ```python |
| from PIL import Image |
| import clip |
| |
| model, tokenizer, img_processor = clip.load("mlx_model") |
| inputs = { |
| "input_ids": tokenizer(["a photo of a cat", "a photo of a dog"]), |
| "pixel_values": img_processor( |
| [Image.open("assets/cat.jpeg"), Image.open("assets/dog.jpeg")] |
| ), |
| } |
| output = model(**inputs) |
| |
| # Get text and image embeddings: |
| text_embeds = output.text_embeds |
| image_embeds = output.image_embeds |
| ``` |
