Update README.md

README.md

@@ -42,6 +42,26 @@ This model was obtained by quantizing weights and activations of [Devstral-Small
 This optimization reduces the number of bits used to represent weights and activations from 16 to 8, reducing GPU memory requirements (by approximately 50%).
 Weight quantization also reduces disk size requirements by approximately 50%.
 
+## Creation
+<details>
+This model was created with [llm-compressor](https://github.com/vllm-project/llm-compressor) by running the code snippet below.
+
+```python
+from transformers import AutoModelForCausalLM
+from llmcompressor import oneshot
+from llmcompressor.modifiers.quantization import QuantizationModifier
+
+
+MODEL_ID = "mistralai/Devstral-Small-2507"
+model = AutoModelForCausalLM.from_pretrained(MODEL_ID, torch_dtype="auto")
+recipe = QuantizationModifier(
+    targets="Linear", scheme="FP8_DYNAMIC", ignore=["lm_head"]
+)
+oneshot(model=model, recipe=recipe)
+SAVE_DIR = MODEL_ID.rstrip("/").split("/")[-1] + "-FP8-Dynamic"
+model.save_pretrained(SAVE_DIR)
+```
+</details>
 
 ## Deployment