Update README.md

README.md

@@ -111,7 +111,7 @@ For local use, applications such as Ollama, LMStudio, MLX-LM, llama.cpp, and KTr
 
 For convenience and performance, we have provided `fp8`-quantized model checkpoint for Qwen3, whose name ends with `-FP8`. The quantization method is fine-grained `fp8` quantization with block size of 128. You can find more details in the `quantization_config` field in `config.json`.
 
-You can use the Qwen3-32B-FP8 model with serveral inference frameworks, including `transformers`, `sglang`, and `vllm`, as the original bfloat16 model.
+You can use the Qwen3-4B-FP8 model with serveral inference frameworks, including `transformers`, `sglang`, and `vllm`, as the original bfloat16 model.
 However, please pay attention to the following known issues:
 - `transformers`:
     - there are currently issues with the "fine-grained fp8" method in `transformers` for distributed inference. You may need to set the environment variable `CUDA_LAUNCH_BLOCKING=1` if multiple devices are used in inference.