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zeromodels/deepseek_vl_1.3b_base

sourceHugging Faceotherupdated 28d agoView on Hugging Face
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Model Card

*See [our collection](https://huggingface.co/collections/zeromodels/deepseek-vl-6a8eae46513968553cfd826d) for all versions of DeepSeek-VL.*

Run DeepSeek-VL with Keras 3: JAX, PyTorch, or TensorFlow

![GitHub](https://github.com/IMvision12/ZeroModels) ![Docs](https://imvision12.github.io/ZeroModels/deepseek_vl/) ![Collection](https://huggingface.co/collections/zeromodels/deepseek-vl-6a8eae46513968553cfd826d)

zeromodels/deepseekvl1.3b_base

Paper: DeepSeek-VL: Towards Real-World Vision-Language Understanding (arXiv:2403.05525) · HF Papers

DeepSeek-VL 1.3B uses a SigLIP @384 tower + 2-linear GELU aligner + Llama decoder for image + text → text. Import from zeromodels.models.deepseek_vl.

For more details on the model, please go to the upstream model card.

Pure-Keras 3 conversion of `deepseek-ai/deepseek-vl-1.3b-base` for zeromodels. One implementation runs unmodified on TensorFlow / Torch / JAX.

This is a vision-language (base) checkpoint (DeepseekVLConditionalGenerate, 1.3B base (SigLIP)).

✨ Quick start

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

from PIL import Image
from zeromodels.models.deepseek_vl import (
    DeepseekVLConditionalGenerate,
    DeepseekVLProcessor,
)

model = DeepseekVLConditionalGenerate.from_weights("zeromodels/deepseek_vl_1.3b_base")
processor = DeepseekVLProcessor.from_weights("zeromodels/deepseek_vl_1.3b_base")

image = Image.open("your_image.jpg")
inputs = processor(
    conversation=[
        {
            "role": "user",
            "content": [
                {"type": "image", "image": image},
                {"type": "text", "text": "Describe this image in one sentence."},
            ],
        }
    ]
)
outputs = model.generate(**inputs, max_new_tokens=64)
print(processor.decode(outputs[0]))

Load any DeepSeek-VL variant the same way with from_weights("zeromodels/<variant>"):

VariantHubNotes
deepseek_vl_1.3b_base`zeromodels/deepseek_vl_1.3b_base`1.3B base
deepseek_vl_1.3b_chat`zeromodels/deepseek_vl_1.3b_chat`1.3B chat
deepseek_vl_7b_base`zeromodels/deepseek_vl_7b_base`7B hybrid base
deepseek_vl_7b_chat`zeromodels/deepseek_vl_7b_chat`7B hybrid chat

Tips

  • Set KERAS_BACKEND before importing Keras / zeromodels.
  • Prefer Processor.from_weights(...) so vision + tokenizer match.
  • 7B hybrid is a different package than 1.3B; do not mix imports.
  • See docs and Loading Weights.
  • Community / upstream safetensors still work via the hf: prefix, e.g. DeepseekVLConditionalGenerate.from_weights("hf:deepseek-ai/deepseek-vl-1.3b-base").

Special Thanks

A huge thank you to the DeepSeek-VL authors for creating and releasing these models.

License: DeepSeek (other / deepseek). See LICENSE.