README.md

---
library_name: transformers
tags: []
---

# Model Card for Ti*k*Zero Adapters
Ti*k*Zero adapters can be loaded into [DeTi*k*Zify<sub>v2</sub>
(8B)](https://huggingface.co/nllg/detikzify-v2-8b), a multimodal language model
that converts sketches and scientific figures into editable,
semantics-preserving TikZ graphics programs, to enable text caption
conditioning. Check out the
[DeTi*k*Zify](https://github.com/potamides/DeTikZify) project for more
information and tips on how to best run the model.

## Usage
The default adapter uses cosine distance training, while an alternative variant
trained with MSE can be loaded by specifying
`adapter_kwargs=dict(revision="mse")` in the `load_adapter` function.

```python
from detikzify.model import load, load_adapter
from detikzify.infer import DetikzifyPipeline

caption = "A multi-layer perceptron with two hidden layers."
pipeline = DetikzifyPipeline(
    *load_adapter(
        *load(
            model_name_or_path="nllg/detikzify-v2-8b",
            device_map="auto",
            torch_dtype="bfloat16",
        ),
        adapter_name_or_path="nllg/tikzero-adapter",
        #adapter_kwargs=dict(revision="mse") # load variant trained with MSE
    )
)

# generate a single TikZ program
fig = pipeline.sample(text=caption)

# if it compiles, rasterize it and show it
if fig.is_rasterizable:
    fig.rasterize().show()
```

## Acknowledgments
This model was trained using computational resources provided by the
bwForCluster Helix, as part of the bwHPC-S5 project. The authors acknowledge
support from the state of Baden-Württemberg through the bwHPC initiative and
the German Research Foundation (DFG) under grant INST 35/1597-1 FUGG.