Update README.md

README.md

@@ -6,26 +6,26 @@ pipeline_tag: text-generation
 base_model:
 - Qwen/Qwen3-Coder-30B-A3B-Instruct
 ---
-# Qwen3-Coder-30B-A3B-Instruct-AWQ
+# Qwen3-Coder-30B-A3B-Instruct-AWQ-4bit
 
 ## Method
-Quantised using [vllm-project/llm-compressor](https://github.com/vllm-project/llm-compressor.git), [nvidia/Llama-Nemotron-Post-Training-Dataset](https://huggingface.co/datasets/nvidia/Llama-Nemotron-Post-Training-Dataset) and the following configs:
+[vllm-project/llm-compressor](https://github.com/vllm-project/llm-compressor.git) and [nvidia/Llama-Nemotron-Post-Training-Dataset](https://huggingface.co/datasets/nvidia/Llama-Nemotron-Post-Training-Dataset) were used to quantize the original model. For further quantization arguments and configurations information, please visit [config.json](https://huggingface.co/cpatonn/Qwen3-Coder-30B-A3B-Instruct-AWQ-4bit/blob/main/config.json) and [recipe.yaml](https://huggingface.co/cpatonn/Qwen3-Coder-30B-A3B-Instruct-AWQ-4bit/blob/main/recipe.yaml).
+
+## Inference
+Please install the latest vllm releases for better support:
 ```
-recipe = [
-    AWQModifier(
-        ignore=["lm_head", "re:.*mlp.gate$", "re:.*mlp.shared_expert_gate$"],
-        scheme="W4A16",
-        targets=["Linear"],  
-    ),
-]
+pip install -U vllm
 ```
-## Inference
 
-### vllm
-Please load the model into vllm and sglang as float16 data type for AWQ support and use `tensor_parallel_size <= 2` i.e.,
+Qwen3-Coder-30B-A3B-Instruct-AWQ-4bit example usage:
 ```
-vllm serve cpatonn/Qwen3-Coder-30B-A3B-Instruct-AWQ-4bit --dtype float16 --tensor-parallel-size 2 --pipeline-parallel-size 2
+vllm serve cpatonn/Qwen3-Coder-30B-A3B-Instruct-AWQ-4bit \
+    --dtype float16 \
+    --tensor-parallel-size 4  \
+    --enable-auto-tool-choice \
+    --tool-call-parser hermes
 ```
+
 # Qwen3-Coder-30B-A3B-Instruct
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