Run InternVL3 with Keras 3: JAX, PyTorch, or TensorFlow

GitHub Docs HuggingFace

kerasformers/internvl3-14b

Pure-Keras 3 conversion of OpenGVLab/InternVL3-14B-hf for kerasformers. 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.

For model details, license, and usage terms, see the upstream model card.

Paper: InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models (arXiv:2504.10479) · HF Papers

Paper: Qwen2.5 Technical Report (arXiv:2412.15115) · HF Papers

✨ Quick start


import os

os.environ["KERAS_BACKEND"] = "torch"  # or "jax" / "tensorflow"

from PIL import Image

from kerasformers.models.internvl import InternVLConditionalGenerate, InternVLProcessor

model = InternVLConditionalGenerate.from_weights("kerasformers/internvl3-14b")

processor = InternVLProcessor.from_weights("kerasformers/internvl3-14b")

inputs = processor(conversation=[

    {"role": "user", "content": [

        {"type": "image", "image": Image.open("photo.jpg")},

        {"type": "text", "text": "Describe this image in one sentence."},

    ]}

])

outputs = model.generate(**inputs, max_new_tokens=64)

print(processor.decode(outputs[0]))

Load any InternVL variant the same way with from_weights("kerasformers/<variant>"). Browse them all in the InternVL collection.

Special Thanks

A huge thank you to the OpenGVLab team for creating and releasing the InternVL models.

License: see the upstream license.

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