Instructions to use zeromodels/deepseek_vl_7b_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/deepseek_vl_7b_base 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/deepseek_vl_7b_base") - Keras
How to use zeromodels/deepseek_vl_7b_base with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://zeromodels/deepseek_vl_7b_base") - Notebooks
- Google Colab
- Kaggle
File size: 679 Bytes
969893a b26f487 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | {
"library_name": "zeromodels",
"zeromodels_version": "1.1.3",
"preprocessor_module": "zeromodels.models.deepseek_vl_hybrid",
"preprocessor_class": "DeepseekVLHybridImageProcessor",
"variant": "deepseek_vl_7b_base",
"size": 384,
"high_res_size": 1024,
"min_size": 14,
"image_mean": [
0.5,
0.5,
0.5
],
"image_std": [
0.5,
0.5,
0.5
],
"high_res_image_mean": [
0.48145466,
0.4578275,
0.40821073
],
"high_res_image_std": [
0.26862954,
0.26130258,
0.27577711
],
"background_color": [
127,
127,
127
],
"high_res_background_color": [
122,
116,
104
],
"data_format": null
} |