Create README.md

README.md

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+Quantized using AutoFP8 with this script:
+
+```python
+from transformers import AutoTokenizer
+import auto_fp8
+from auto_fp8 import AutoFP8ForCausalLM, BaseQuantizeConfig
+
+pretrained_model_dir = "ibm-granite/granite-20b-code-base"
+quantized_model_dir = "granite-20b-code-base-FP8"
+
+tokenizer = AutoTokenizer.from_pretrained(pretrained_model_dir, use_fast=True)
+
+# use some code to calibrate
+import auto_fp8
+tmp = auto_fp8.__file__.split('/')[:-1]
+tmp.append('quantize.py')
+seed_text_file = '/'.join(tmp)
+
+with open(seed_text_file, "r") as f:
+    text = f.read()
+
+examples = [text]
+
+examples = tokenizer(examples, return_tensors="pt").to("cuda")
+
+quantize_config = BaseQuantizeConfig(
+    quant_method="fp8",
+    activation_scheme="static",
+    ignore_patterns=["re:.*lm_head"],
+)
+
+model = AutoFP8ForCausalLM.from_pretrained(
+    pretrained_model_dir, quantize_config=quantize_config
+)
+
+model.quantize(examples)
+model.save_quantized(quantized_model_dir)
+```