Improve model card: Update paper link, license, add library_name and sample usage

README.md

@@ -1,12 +1,15 @@
 ---
-license: other
-license_name: qwen
-license_link: LICENSE
-datasets:
-- julien31/soar_arc_train_5M
 base_model:
 - Qwen/Qwen2.5-72B-Instruct
+datasets:
+- julien31/soar_arc_train_5M
+license: apache-2.0
+language:
+- en
+metrics:
+- accuracy
 pipeline_tag: text-generation
+library_name: transformers
 tags:
 - text-generation
 - code-generation
@@ -16,15 +19,16 @@ tags:
 - arc-agi
 - soar
 ---
+
 # SOAR-ARC Models: Self-Improving Language Models for Program Synthesis
 
 <p align="center">
-          🤗 <a href="https://huggingface.co/collections/julien31/soar-arc-6856d27681fce01d9af4c4a3">Hugging Face (data and model)</a>&nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://icml.cc/virtual/2025/poster/43499">Paper</a> &nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://julienp.netlify.app/posts/soar/">Blog</a>
+          🤗 <a href="https://huggingface.co/collections/julien31/soar-arc-6856d27681fce01d9af4c4a3">Hugging Face (data and model)</a>&nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://huggingface.co/papers/2507.14172">Paper</a> &nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://julienp.netlify.app/posts/soar/">Blog</a>
 </p>
 
 This repository contains one of the models fine-tuned using the **SOAR** (**S**elf-improving **O**perators for **A**utomated program **R**efinements) framework, as presented in the paper:
 
-> [**Self-Improving Language Models for Evolutionary Program Synthesis: A Case Study on ARC-AGI**](https://icml.cc/virtual/2025/poster/43499)
+> [**Self-Improving Language Models for Evolutionary Program Synthesis: A Case Study on ARC-AGI**](https://huggingface.co/papers/2507.14172)
 >
 > Julien Pourcel, Cédric Colas, Pierre-Yves Oudeyer.
 > *Proceedings of the 42nd International Conference on Machine Learning (ICML), 2025.*
@@ -66,10 +70,61 @@ This process creates a powerful feedback loop: the fine-tuned model becomes bett
 
 The primary use of this model is to generate a Python function that solves an ARC task. The input to the model should be a formatted prompt containing the training and test examples of the ARC task.
 
+You can load the model using the `transformers` library:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "julien31/Soar-qwen-72b"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16, # or torch.float16 if bfloat16 is not supported by your GPU
+    device_map="auto",
+)
+
+# Example prompt structure for an ARC task (simplified)
+# For full ARC problem formatting and inference details, 
+# refer to the official SOAR repository and notebook.
+prompt = """
+Below are examples of input-output pairs for an ARC task:
+
+Input: [[0,0,0,0,0],[0,0,0,0,0],[0,0,1,0,0],[0,0,0,0,0],[0,0,0,0,0]]
+Output: [[0,0,0,0,0],[0,0,0,0,0],[0,0,0,0,0],[0,0,0,0,0],[0,0,0,0,0]]
+
+Write a Python function `solve(input_grid)` that transforms the input grid based on the provided examples.
+```python
+def solve(input_grid):
+    # Your code here
+```
+"""
+
+messages = [
+    {"role": "user", "content": prompt},
+]
+
+# Apply chat template (Qwen2.5 chat format)
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+# Generate code
+generated_ids = model.generate(
+    model_inputs.input_ids,
+    max_new_tokens=512,
+    do_sample=True,
+    temperature=0.7,
+    top_p=0.8,
+)
+
+generated_text = tokenizer.batch_decode(generated_ids[:, model_inputs.input_ids.shape[1]:], skip_special_tokens=True)[0]
+print(generated_text)
+```
+
 For a complete, end-to-end example of how to format the prompt, run inference, execute the generated code, and visualize the results, please refer to the official repository and notebook:
 
 *   **Official SOAR GitHub Repository**: [https://github.com/flowersteam/SOAR](https://github.com/flowersteam/SOAR)
 *   **Inference & Visualization Notebook**: [https://github.com/flowersteam/SOAR/blob/main/notebook/inference_visualisation.ipynb](https://github.com/flowersteam/SOAR/blob/main/notebook/inference_visualisation.ipynb)
 
-<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/made with unsloth.png" width="20%" />
-
+<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/made%20with%20unsloth.png" width="20%" />