Update README.md

README.md

@@ -15,4 +15,36 @@ tags:
 - llama
 - llama-3
 - pytorch
----
+---
+
+Model is quantized to FP8 using llm_compressor.
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from llmcompressor.transformers import oneshot
+from llmcompressor.modifiers.quantization import QuantizationModifier
+
+# Define the model ID for the model you want to quantize
+MODEL_ID = "meta-llama/Llama-3.2-1B-Instruct"
+
+# Load the model and tokenizer
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_ID, device_map="auto", torch_dtype="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+
+# Configure the quantization recipe
+recipe = QuantizationModifier(targets="Linear", scheme="FP8_DYNAMIC", ignore=["lm_head"])
+
+# Apply the quantization algorithm
+oneshot(model=model, recipe=recipe)
+
+# Define the directory to save the quantized model
+SAVE_DIR = MODEL_ID.split("/")[1] + "-FP8-Dynamic"
+
+# Save the quantized model and tokenizer
+model.save_pretrained(SAVE_DIR)
+tokenizer.save_pretrained(SAVE_DIR)
+
+print(f"Quantized model saved to (SAVE_DIR)")
+```