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OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs.
Passed 23 of 24 test cases with the skill, and 19 of 24 without it.
and 4 more in the full report
5 fixed18 passed either way0 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
I am choosing between CLIP architecture options for a production application that needs a solid balance of quality and speed. Which model string should I pass into the load function as the default recommendation?
| Checked | Without skill | With skill |
|---|---|---|
| The response specifies `ViT-B/32` as the recommended default model. | Missed | Passed |
The instructions your model reads when the skill loads.
OpenAI's model that understands images from natural language.
Use when:
Metrics:
Use alternatives instead:
pip install git+https://github.com/openai/CLIP.git
pip install torch torchvision ftfy regex tqdm
import torch
import clip
from PIL import Image
test cases passed, vs 19 / 24 without
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