Instructions to use GMLHUHE/PsyLLM-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use GMLHUHE/PsyLLM-4B with Transformers:

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

pipe = pipeline("text-generation", model="GMLHUHE/PsyLLM-4B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("GMLHUHE/PsyLLM-4B")
model = AutoModelForCausalLM.from_pretrained("GMLHUHE/PsyLLM-4B")
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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use GMLHUHE/PsyLLM-4B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "GMLHUHE/PsyLLM-4B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "GMLHUHE/PsyLLM-4B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/GMLHUHE/PsyLLM-4B

SGLang

How to use GMLHUHE/PsyLLM-4B 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 "GMLHUHE/PsyLLM-4B" \
    --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": "GMLHUHE/PsyLLM-4B",
		"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 "GMLHUHE/PsyLLM-4B" \
        --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": "GMLHUHE/PsyLLM-4B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use GMLHUHE/PsyLLM-4B with Docker Model Runner:
```
docker model run hf.co/GMLHUHE/PsyLLM-4B
```

GMLHUHE commited on Jan 24

Commit

e2a03c0

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Update README.md

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@@ -7,8 +7,20 @@ tags:
 - full
 - generated_from_trainer
 ---
-[![arXiv](https://img.shields.io/badge/arXiv-2502.04424-b31b1b.svg)](https://arxiv.org/pdf/2505.15715v2)
-[![GitHub](https://img.shields.io/badge/GitHub-Emo--gml/PsyLLM-blue?logo=github)](https://github.com/Emo-gml/PsyLLM)
 **PsyLLM** is a large language model designed for **psychological counseling and mental health dialogue generation**. It integrates **diagnostic reasoning** and **therapeutic reasoning**, following established frameworks such as **DSM/ICD**, and incorporates diverse therapeutic approaches including **CBT**, **ACT**, and **psychodynamic therapy**.

 - full
 - generated_from_trainer
 ---
+<p align="center">
+  <img src="https://huggingface.co/GMLHUHE/PsyLLM-8B/resolve/main/logo.jpg"
+       alt="PsyLLM logo"
+       width="200px" />
+</p>
+<p align="center">
+  <a href="https://arxiv.org/pdf/2505.15715v2">
+    <img src="https://img.shields.io/badge/arXiv-2505.15715-b31b1b.svg" alt="arXiv">
+  </a>
+  <a href="https://github.com/Emo-gml/PsyLLM">
+    <img src="https://img.shields.io/badge/GitHub-Emo--gml%2FPsyLLM-blue?logo=github" alt="GitHub">
+  </a>
+</p>
 **PsyLLM** is a large language model designed for **psychological counseling and mental health dialogue generation**. It integrates **diagnostic reasoning** and **therapeutic reasoning**, following established frameworks such as **DSM/ICD**, and incorporates diverse therapeutic approaches including **CBT**, **ACT**, and **psychodynamic therapy**.