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OpenGVLab/InternVL3-8B-hf for zeromodels. One implementation runs unmodified on TensorFlow / Torch / JAX. This is a InternVL3 checkpoint, served as image + text -> text via InternVLProcessor; weights are stored in bfloat16.1
2import os
3
4os.environ["KERAS_BACKEND"] = "torch" # or "jax" / "tensorflow"
5
6from PIL import Image
7
8from zeromodels.models.internvl import InternVLConditionalGenerate, InternVLProcessor
9
10model = InternVLConditionalGenerate.from_weights("zeromodels/internvl3-8b")
11
12processor = InternVLProcessor.from_weights("zeromodels/internvl3-8b")
13
14inputs = processor(conversation=[
15
16 {"role": "user", "content": [
17
18 {"type": "image", "image": Image.open("photo.jpg")},
19
20 {"type": "text", "text": "Describe this image in one sentence."},
21
22 ]}
23
24])
25
26outputs = model.generate(**inputs, max_new_tokens=64)
27
28print(processor.decode(outputs[0]))
29from_weights("zeromodels/<variant>"). Browse them all in the InternVL collection.