Create README.md

README.md

@@ -0,0 +1,36 @@
+---
+license: gemma
+base_model:
+- google/gemma-2-27b-it
+---
+
+FP-8 quantized version of google/gemma-2-27b-it quantized with **compute sponsored by Arrow and Nvidia through Danish Data Science Community**. 
+
+Quantized using this script: 
+
+```python
+from llmcompressor.transformers import SparseAutoModelForCausalLM
+from transformers import AutoTokenizer
+from llmcompressor.transformers import oneshot
+from llmcompressor.modifiers.quantization import QuantizationModifier
+
+
+MODEL_ID = "google/gemma-2-27b-it"
+
+model = SparseAutoModelForCausalLM.from_pretrained(
+  MODEL_ID, device_map="auto", torch_dtype="auto")
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+
+
+# Configure the simple PTQ quantization
+recipe = QuantizationModifier(
+  targets="Linear", scheme="FP8_DYNAMIC", ignore=["lm_head"])
+
+# Apply the quantization algorithm.
+oneshot(model=model, recipe=recipe)
+
+# Save the model.
+SAVE_DIR = MODEL_ID.split("/")[1] + "-FP8-Dynamic"
+model.save_pretrained(SAVE_DIR)
+tokenizer.save_pretrained(SAVE_DIR)
+```