aimv2-large-patch14-336

Name: aimv2-large-patch14-336
Author: apple

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apple

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Quick Summary

We introduce the AIMv2 family of vision models pre-trained with a multimodal autoregressive objective.

Code Examples

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

Usagepythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    revision="639423ae9f07319d24a7fc431b61908110d08d3a",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

JAXpythontransformers

import requests
from PIL import Image
from transformers import AutoImageProcessor, FlaxAutoModel

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained(
    "apple/aimv2-large-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-large-patch14-336",
    trust_remote_code=True,
)

inputs = processor(images=image, return_tensors="jax")
outputs = model(**inputs)

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