Instructions to use zerofata/MS3.2-PaintedFantasy-24B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zerofata/MS3.2-PaintedFantasy-24B with Transformers:

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

pipe = pipeline("text-generation", model="zerofata/MS3.2-PaintedFantasy-24B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("zerofata/MS3.2-PaintedFantasy-24B")
model = AutoModelForCausalLM.from_pretrained("zerofata/MS3.2-PaintedFantasy-24B")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use zerofata/MS3.2-PaintedFantasy-24B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zerofata/MS3.2-PaintedFantasy-24B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zerofata/MS3.2-PaintedFantasy-24B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/zerofata/MS3.2-PaintedFantasy-24B

SGLang

How to use zerofata/MS3.2-PaintedFantasy-24B 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 "zerofata/MS3.2-PaintedFantasy-24B" \
    --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": "zerofata/MS3.2-PaintedFantasy-24B",
		"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 "zerofata/MS3.2-PaintedFantasy-24B" \
        --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": "zerofata/MS3.2-PaintedFantasy-24B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use zerofata/MS3.2-PaintedFantasy-24B with Docker Model Runner:
```
docker model run hf.co/zerofata/MS3.2-PaintedFantasy-24B
```

My firs impression

by Emalog - opened Jul 6, 2025

Discussion

Emalog

Jul 6, 2025

•

edited Jul 6, 2025

This model is a very pleasant surprise. I like that it always writes as much as it needs to.
It has an interesting but pleasant style that is different from other LLMs I have used.
The modell skilfully and well pursues your plots, and I like that he spices up the roleplay by noting the little details.

As RP progresses, the model's adherence to character traits deteriorates significantly (after 4000token context), which is surprisingly bad for a 24b model.
This model is it ignored parts of the character description content several times. I brought this to the model's attention (OOC) and the model admitted that it was wrong.

ThijsL202

Jul 9, 2025

•

edited Jul 9, 2025

As RP progresses, the model's adherence to character traits deteriorates significantly (after 4000token context), which is surprisingly bad for a 24b model.
This model is it ignored parts of the character description content several times. I brought this to the model's attention (OOC) and the model admitted that it was wrong.

Same experience here.
EDIT:
Sometimes it works pretty well, but most of the time it starts to forget stuff, not even a few messages in... Woops, wrong repo. I don't know why Huggingface keeps sending me to this one. I'm experiencing this with I'm using zerofata_MS3.2-PaintedFantasy-Visage-33B-Q6_K_L.kcpps from

Karlmeister

Jul 9, 2025

•

edited Jul 9, 2025

One of the best 22b/24b models I've tried lately. Consistent and with a nice dosage of creativity, action and something I've seen other models lack: char proactivity bounded by their traits... until certain context threshold (in my case, around 8K-9K). Not only it tends to forget char traits, starts to lose consistency and time-spacial awareness - specially when more "npc" or actions happen in different places. It also starts to repeat text, phrases and patterns. If these issues could be addressed, we could have between hands one of the best - if not the best 24b model to Rp. (IMO), this potential "fixed" version could be better even that ChatWaifu 22b, Gaslit Abomination 24b and BrokenTutu 24b (my favs in the last months).

BTW I'm using mradermacher imatrix quants (Q4_K_M & Q6_K).

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment