metadata
license: apache-2.0
base_model: ThinkMorph/ThinkMorph-SSL-Base
base_model_relation: finetune
pipeline_tag: any-to-any
library_name: bagel
datasets:
- ThinkMorph/Pretext-270K
- ThinkMorph/Instruct-180K
ThinkMorph-SSL-Instruct
About
ThinkMorph-SSL-Instruct reasons with interleaved text and images. On a visual question it thinks in text, generates intermediate images when they help (a zoomed-in crop, a depth map, a bird's-eye view, the view from another position), and then answers.
It is trained from BAGEL-7B-MoT in two stages:
| Stage | Data | Model |
|---|---|---|
| 1. Self-supervised pretext reasoning | Pretext-270K | ThinkMorph-SSL-Base |
| 2. Instruction tuning | Instruct-180K | ThinkMorph-SSL-Instruct (this model) |
Usage
The checkpoint has the same layout as BAGEL-7B-MoT and loads with the BAGEL code. Keep the VAE and tokenizer files shipped here. Prompt the model with the system prompt it was trained with:
Use <think>...</think> for intermediate reasoning or planning.
To generate an image, write <gen_image> followed by an image-size declaration:
<gen_image>[Image size: (height, width)]
Generated images become part of your context and can inform subsequent reasoning. You may generate more than one image if needed.
If the task requires a final textual answer, wrap it in <answer>...</answer>.
If no textual answer is needed, the response may end after reasoning or image generation.
Example:
<think>reasoning step</think>
<gen_image>[Image size: (512, 512)]
<think>observe and reason about the generated image</think>
<answer>final answer</answer>
Benchmarks
Results will be added with the paper.
Citation
The citation will be added with the paper.