Update README.md

README.md

@@ -32,6 +32,9 @@ library_name: transformers
 
 # ERNIE-4.5-300B-A47B-Base
 
+> [!NOTE]
+> Note: "**-Paddle**" models use [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) weights, while "**-PT**" models use Transformer-style PyTorch weights.
+
 ## ERNIE 4.5 Highlights
 
 The advanced capabilities of the ERNIE 4.5 models, particularly the MoE-based A47B and A3B series, are underpinned by several key technical innovations:
@@ -61,41 +64,6 @@ ERNIE-4.5-300B-A47B-Base is a text MoE Base model, with 300B total parameters an
 
 ## Quickstart
 
-### Model Finetuning with ERNIEKit
-
-[ERNIEKit](https://github.com/PaddlePaddle/ERNIE) is a training toolkit based on PaddlePaddle, specifically designed for the ERNIE series of open-source large models. It provides comprehensive support for scenarios such as instruction fine-tuning (SFT, LoRA) and alignment training (DPO), ensuring optimal performance.
-
-Usage Examples:
-
-```bash
-# Download model
-huggingface-cli download baidu/ERNIE-4.5-300B-A47B-Base-Paddle --local-dir baidu/ERNIE-4.5-300B-A47B-Base-Paddle
-# SFT
-erniekit train examples/configs/ERNIE-4.5-300B-A47B/sft/run_sft_wint8mix_lora_8k.yaml model_name_or_path=baidu/ERNIE-4.5-300B-A47B-Base-Paddle
-# DPO
-erniekit train examples/configs/ERNIE-4.5-300B-A47B/dpo/run_dpo_wint8mix_lora_8k.yaml model_name_or_path=baidu/ERNIE-4.5-300B-A47B-Base-Paddle
-```
-
-For more detailed examples, including SFT with LoRA, multi-GPU configurations, and advanced scripts, please refer to the examples folder within the [ERNIEKit](https://github.com/PaddlePaddle/ERNIE) repository.
-
-### Using FastDeploy
-
-Service deployment can be quickly completed using FastDeploy in the following command. For more detailed usage instructions, please refer to the [FastDeploy Repository](https://github.com/PaddlePaddle/FastDeploy).
-
-**Note**: To deploy on a configuration with 4 GPUs each having at least 80G of memory, specify ```--quantization wint4```. If you specify ```--quantization wint8```, then resources for 8 GPUs are required.
-
-```bash
-python -m fastdeploy.entrypoints.openai.api_server \
-       --model baidu/ERNIE-4.5-300B-A47B-Base-Paddle \
-       --port 8180 \
-       --metrics-port 8181 \
-       --engine-worker-queue-port 8182 \
-       --quantization wint4 \
-       --tensor-parallel-size 8 \
-       --max-model-len 32768 \
-       --max-num-seqs 32
-```
-
 ### Using `transformers` library
 
 **Note**: Before using the model, please ensure you have the `transformers` library installed (version 4.50.0 or higher)