Image-Text-to-Text
ZeroModels
Keras
PyTorch
JAX
TensorFlow
English
qwen3_vl_moe
qwen3-vl-moe
multimodal
vision
mixture-of-experts
Instructions to use zeromodels/qwen3-vl-30b-a3b-thinking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/qwen3-vl-30b-a3b-thinking with ZeroModels:
# pip install -U zeromodels # ZeroModels is pure Keras 3, so pick a backend: "jax", "torch" or "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" from zeromodels import AutoZModel # AutoZModel reads the repo's model_type and loads the matching class. # For a task head use the matching loader, e.g. AutoZMImageClassify / AutoZMDetect / # AutoZMSemanticSegment / AutoZMTextGenerate (see zeromodels.auto). model = AutoZModel.from_weights("zeromodels/qwen3-vl-30b-a3b-thinking") - Keras
How to use zeromodels/qwen3-vl-30b-a3b-thinking with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://zeromodels/qwen3-vl-30b-a3b-thinking") - Notebooks
- Google Colab
- Kaggle
File size: 432 Bytes
911bfb0 23260bd 911bfb0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"library_name": "zeromodels",
"zeromodels_version": "1.2.2",
"preprocessor_module": "zeromodels.models.qwen2_vl",
"preprocessor_class": "Qwen2VLImageProcessor",
"variant": "qwen3-vl-30b-a3b-thinking",
"patch_size": 14,
"spatial_merge_size": 2,
"temporal_patch_size": 2,
"min_pixels": 3136,
"max_pixels": 1003520,
"image_mean": [
0.5,
0.5,
0.5
],
"image_std": [
0.5,
0.5,
0.5
]
} |