Instructions to use baidu/ERNIE-4.5-300B-A47B-Base-PT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use baidu/ERNIE-4.5-300B-A47B-Base-PT with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="baidu/ERNIE-4.5-300B-A47B-Base-PT")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("baidu/ERNIE-4.5-300B-A47B-Base-PT")
model = AutoModelForCausalLM.from_pretrained("baidu/ERNIE-4.5-300B-A47B-Base-PT", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use baidu/ERNIE-4.5-300B-A47B-Base-PT with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "baidu/ERNIE-4.5-300B-A47B-Base-PT"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "baidu/ERNIE-4.5-300B-A47B-Base-PT",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/baidu/ERNIE-4.5-300B-A47B-Base-PT

SGLang

How to use baidu/ERNIE-4.5-300B-A47B-Base-PT with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "baidu/ERNIE-4.5-300B-A47B-Base-PT" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "baidu/ERNIE-4.5-300B-A47B-Base-PT",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "baidu/ERNIE-4.5-300B-A47B-Base-PT" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "baidu/ERNIE-4.5-300B-A47B-Base-PT",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use baidu/ERNIE-4.5-300B-A47B-Base-PT with Docker Model Runner:
```
docker model run hf.co/baidu/ERNIE-4.5-300B-A47B-Base-PT
```

jzhang533

sunzhongkai588 commited on Jul 4, 2025

Commit

cb278bc

verified ·

1 Parent(s): f0c882d

Update README.md (#2)

Browse files

- Update README.md (9bf6dd7e43f9cba4fae872caa3157b74f2da378c)

Co-authored-by: Suen.ZK <sunzhongkai588@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +3 -35

README.md CHANGED Viewed

@@ -32,6 +32,9 @@ library_name: transformers
 # ERNIE-4.5-300B-A47B-Base
 ## 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)

 # 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:
 ## Quickstart
 ### Using `transformers` library
 **Note**: Before using the model, please ensure you have the `transformers` library installed (version 4.50.0 or higher)