init v0.23.0

Signed-off-by: Sun Ruoxi <sunruoxi@4paradigm.com>

examples/quantization/llm-compressor/w4a8_dynamic_moe.py

@@ -0,0 +1,58 @@
+from llmcompressor import oneshot
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+MODEL_ID = "Qwen/Qwen3-30B-A3B-Instruct-2507"
+
+# Load model.
+model = AutoModelForCausalLM.from_pretrained(MODEL_ID, torch_dtype="auto")
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+
+recipe = """
+quant_stage:
+    quant_modifiers:
+        QuantizationModifier:
+            ignore: ["lm_head", "re:.*mlp.gate$"]
+            config_groups:
+                group_0:
+                    weights:
+                        num_bits: 8
+                        type: int
+                        strategy: channel
+                        dynamic: false
+                        symmetric: true
+                    input_activations:
+                        num_bits: 8
+                        type: int
+                        strategy: token
+                        dynamic: true
+                        symmetric: true
+                    targets: ["re:.*self_attn.k_proj.*", "re:.*self_attn.o_proj.*",
+                        "re:.*self_attn.q_proj.*", "re:.*self_attn.v_proj.*"]
+                group_1:
+                    weights:
+                        num_bits: 4
+                        type: int
+                        strategy: group
+                        group_size: 128
+                        dynamic: false
+                        symmetric: true
+                    input_activations:
+                        num_bits: 8
+                        type: int
+                        strategy: token
+                        dynamic: true
+                        symmetric: true
+                    targets: ["re:.*down_proj.*", "re:.*gate_proj.*", "re:.*up_proj.*"]
+"""
+
+# Apply quantization.
+oneshot(
+    model=model,
+    recipe=recipe,
+    trust_remote_code_model=True,
+)
+
+# Save to disk in compressed-tensors format.
+SAVE_DIR = MODEL_ID.rstrip("/").split("/")[-1] + "-W4A8"
+model.save_pretrained(SAVE_DIR, save_compressed=True)
+tokenizer.save_pretrained(SAVE_DIR)