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kerasformers/
deepseek_vl_1.3b_chat

Name: deepseek_vl_1.3b_chat
Availability: InStock

deepseek-ai/deepseek-vl-1.3b-chat

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

GitHub

zeromodels/deepseek_vl_1.3b_chat

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-chat for zeromodels. One implementation runs unmodified on TensorFlow / Torch / JAX.

This is a vision-language (chat) checkpoint (DeepseekVLConditionalGenerate, 1.3B chat (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_chat")
processor = DeepseekVLProcessor.from_weights("zeromodels/deepseek_vl_1.3b_chat")

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>"):

Variant	Hub	Notes
`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-chat").

Special Thanks

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

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

kerasformers/deepseek_vl_1.3b_chat