aimv2-3B-patch14-336

20
4
—
by
apple
Image Model
OTHER
3B params
New
20 downloads
Early-stage
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Edge AI:
Mobile
Laptop
Server
7GB+ RAM
Mobile
Laptop
Server
Quick Summary

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

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
3GB+ RAM

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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
)
model = AutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    revision="d1adb39ee92dfd7ecf3114b1ee3aa7e9027ce98f",
    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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-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/aimv2-3B-patch14-336",
)
model = FlaxAutoModel.from_pretrained(
    "apple/aimv2-3B-patch14-336",
    trust_remote_code=True,
)

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

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