Instructions to use kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2 with Transformers:

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

pipe = pipeline("text-generation", model="kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2")
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("kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2")
model = AutoModelForCausalLM.from_pretrained("kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2", 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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2

SGLang

How to use kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2 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 "kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2" \
    --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": "kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2",
		"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 "kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2" \
        --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": "kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2 with Docker Model Runner:
```
docker model run hf.co/kxdw2580/Qwen2.5-3B-Instruct-Catgirl-v2
```

lbourdois commited on Apr 28, 2025

Commit

dd6f4a5

verified ·

1 Parent(s): 14feac7

Improve language tag

Browse files

Hi! As the model is multilingual, this is a PR to add other languages than English to the language tag to improve the referencing. Note that 29 languages are announced in the README, but only 13 are explicitly listed. I was therefore only able to add these 13 languages.

Files changed (1) hide show

README.md +51 -39

README.md CHANGED Viewed

@@ -1,39 +1,51 @@
----
-library_name: transformers
-tags:
-- llama-factory
-license: apache-2.0
-language:
-- zh
-base_model:
-- Qwen/Qwen2.5-3B-Instruct
-pipeline_tag: text-generation
-datasets:
-- kxdw2580/catgirl-dataset
----
-# Model Card for Qwen2.5-3B-Instruct-Catgirl-v2
-<!-- Provide a quick summary of what the model is/does. -->
-[README_translate.md](README_translate.md)    [README_zh.md](README_zh.md)
-## Test model
-Now you can [use this space](https://huggingface.co/spaces/kxdw2580/Test-my-models) to try our model
-But this space just use cpu,so it will so slow.I don't have enough money,sorry.
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-This is the second generation model of [this model](https://huggingface.co/kxdw2580/Qwen2.5-3B-Instruct-Catgirl-chinese).
-- **Developed by:** kxdw2580
-- **Model type:** 3B
-- **Language(s) (NLP):** Chinese(best),English,etc.
-- **Finetuned from model :** Qwen/Qwen2.5-3B-Instruct

+---
+library_name: transformers
+tags:
+- llama-factory
+license: apache-2.0
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+base_model:
+- Qwen/Qwen2.5-3B-Instruct
+pipeline_tag: text-generation
+datasets:
+- kxdw2580/catgirl-dataset
+---
+# Model Card for Qwen2.5-3B-Instruct-Catgirl-v2
+<!-- Provide a quick summary of what the model is/does. -->
+[README_translate.md](README_translate.md)    [README_zh.md](README_zh.md)
+## Test model
+Now you can [use this space](https://huggingface.co/spaces/kxdw2580/Test-my-models) to try our model
+But this space just use cpu,so it will so slow.I don't have enough money,sorry.
+## Model Details
+### Model Description
+<!-- Provide a longer summary of what this model is. -->
+This is the second generation model of [this model](https://huggingface.co/kxdw2580/Qwen2.5-3B-Instruct-Catgirl-chinese).
+- **Developed by:** kxdw2580
+- **Model type:** 3B
+- **Language(s) (NLP):** Chinese(best),English,etc.
+- **Finetuned from model :** Qwen/Qwen2.5-3B-Instruct