Not-For-All-Audiences

Instructions to use sophosympatheia/Mero-Artemis-31B-v0.3.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sophosympatheia/Mero-Artemis-31B-v0.3.1 with Transformers:

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

pipe = pipeline("image-text-to-text", model="sophosympatheia/Mero-Artemis-31B-v0.3.1")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("sophosympatheia/Mero-Artemis-31B-v0.3.1")
model = AutoModelForMultimodalLM.from_pretrained("sophosympatheia/Mero-Artemis-31B-v0.3.1")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use sophosympatheia/Mero-Artemis-31B-v0.3.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sophosympatheia/Mero-Artemis-31B-v0.3.1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sophosympatheia/Mero-Artemis-31B-v0.3.1",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/sophosympatheia/Mero-Artemis-31B-v0.3.1

SGLang

How to use sophosympatheia/Mero-Artemis-31B-v0.3.1 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 "sophosympatheia/Mero-Artemis-31B-v0.3.1" \
    --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": "sophosympatheia/Mero-Artemis-31B-v0.3.1",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "sophosympatheia/Mero-Artemis-31B-v0.3.1" \
        --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": "sophosympatheia/Mero-Artemis-31B-v0.3.1",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use sophosympatheia/Mero-Artemis-31B-v0.3.1 with Docker Model Runner:
```
docker model run hf.co/sophosympatheia/Mero-Artemis-31B-v0.3.1
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Mero-Artemis-31B-v0.3.1

This is an experimental merge of BeaverAI/Artemis-31B-v1h-GGUF with zerofata/G4-MeroMero-31B. TheDrummer (creator of Artemis) has not released the full precision FP16 weights for the Artemis v1h model, so I had to get creative with a Q8_0 GGUF file to produce this merge. There is some precision loss in doing that, but Q8_0 is already pretty close to FP16 in practice, and I think the noise effectively washes out during the merge process.

After several experiments, I think this merge turned out nicely. I wanted to capture the personality and style of Artemis while preserving MeroMero's excellent attention to details, and I think this version is close to the target. There are a few GGUFs ready for testing in the GGUFs branch of this repo.

Since this is an experiment right now, I'm not going to add all my ususal fluff about recommended settings. If the community likes this model, I might give it a proper release later.