Update README.md

README.md

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----
-license: other
-license_name: deepseek
-license_link: >-
-  https://raw.githubusercontent.com/deepseek-ai/DeepSeek-Coder/main/LICENSE-MODEL
----
+---
+license: other
+license_name: deepseek
+license_link: >-
+  https://raw.githubusercontent.com/deepseek-ai/DeepSeek-Coder/main/LICENSE-MODEL
+datasets:
+- nllg/datikz-v2
+---
+
+# Model Card for DeTi*k*Zify-DS<sub>1.3b</sub>
+DeTi*k*Zify-TL<sub>1.1b</sub> is a language model that automatically converts
+sketches and existing scientific figures into editable, semantics-preserving
+Ti*k*Z graphics programs. It is based on [DeepSeek Coder
+1.3b](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) and was
+fine-tuned on
+[DaTi*k*Z<sub>v2</sub>](https://huggingface.co/datasets/nllg/datikz-v2). 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
+```python
+from operator import itemgetter
+
+from detikzify.model import load
+from detikzify.infer import DetikzifyPipeline
+import torch
+
+image = "https://w.wiki/A7Cc"
+pipeline = DetikzifyPipeline(*load(
+    base_model="nllg/detikzify-ds-1.3b",
+    device_map="auto",
+    torch_dtype=torch.bfloat16,
+))
+
+# generate a single TikZ program
+fig = pipeline.sample(image=image)
+
+# if it compiles, rasterize it and show it
+if fig.is_rasterizable:
+    fig.rasterize().show()
+
+# run MCTS for 10 minutes and generate multiple TikZ programs
+figs = set()
+for score, fig in pipeline.simulate(image=image, timeout=600):
+    figs.add((score, fig))
+
+# save the best TikZ program
+best = sorted(figs, key=itemgetter(0))[-1][1]
+best.save("fig.tex")
+```