System Info

• transformers version: 4.43.0
• Platform: macOS-13.0-arm64-arm-64bit
• Python version: 3.10.9
• Huggingface_hub version: 0.24.6
• Safetensors version: 0.4.5
• Accelerate version: not installed
• Accelerate config: not found
• PyTorch version (GPU?): 2.4.1 (False)
• Tensorflow version (GPU?): not installed (NA)
• Flax version (CPU?/GPU?/TPU?): not installed (NA)
• Jax version: not installed
• JaxLib version: not installed
• Using distributed or parallel set-up in script?:

Who can help?

@ArthurZucker

Information

• The official example scripts
• My own modified scripts

Tasks

• An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
• My own task or dataset (give details below)

Reproduction

from transformers import CLIPModel, CLIPTokenizerFast

tokenizer = CLIPTokenizerFast.from_pretrained("patrickjohncyh/fashion-clip")
model = CLIPModel.from_pretrained("patrickjohncyh/fashion-clip")

tokenized = tokenizer(["hello"], return_tensors="pt", padding=True)
print("tokenized", tokenized)

# bus error occurs here
embed = model.get_text_features(**tokenized).detach().cpu().numpy()
print("embedded", tokenized)

gives :

tokenized {'input_ids': tensor([[49406,  3497, 49407]]), 'attention_mask': tensor([[1, 1, 1]])}
zsh: bus error  python test_hf.py

I don't think the issue has been posted already.
After bisecting versions, it looks like 4.42.4 does not have the issue and 4.43.0 has the issue

I have little insight to provide except the bus error, and that this does not occur with the clip-vit-base-patch32 model.
I saw some breaking changes in this version release, but only about the tokenizer.
I did not have time to test on a linux distribution yet

Thanks !

Expected behavior

By using the exact same script with the hugging face CLIP pretrained model, the embedding get computed as they should

processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
tokenizer = CLIPTokenizerFast.from_pretrained("openai/clip-vit-base-patch32")