Instructions to use OddTheGreat/Mars_27B_V.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OddTheGreat/Mars_27B_V.1 with Transformers:

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

pipe = pipeline("image-text-to-text", model="OddTheGreat/Mars_27B_V.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("OddTheGreat/Mars_27B_V.1")
model = AutoModelForMultimodalLM.from_pretrained("OddTheGreat/Mars_27B_V.1", device_map="auto")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use OddTheGreat/Mars_27B_V.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OddTheGreat/Mars_27B_V.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": "OddTheGreat/Mars_27B_V.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/OddTheGreat/Mars_27B_V.1

SGLang

How to use OddTheGreat/Mars_27B_V.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 "OddTheGreat/Mars_27B_V.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": "OddTheGreat/Mars_27B_V.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 "OddTheGreat/Mars_27B_V.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": "OddTheGreat/Mars_27B_V.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 OddTheGreat/Mars_27B_V.1 with Docker Model Runner:
```
docker model run hf.co/OddTheGreat/Mars_27B_V.1
```

Custom Finetune of Gemma27

by Ful3 - opened Jan 14

Discussion

Ful3

Jan 14

Hi OddTheGreat,

First of all great work on Mars model. I have tested a few of Gemma27 model and this is so far the best

I have a fairly specific challenge I’d like to run by you. We’re looking to contract someone with hands-on fine-tuning experience, and we’d of course cover your time as well as any training resources needed.

Here’s the situation:

We’re currently using a fine-tuned version of Llama 3.3 70B. It has an excellent writing tone and produces great responses, but it struggles with non-English languages, its attention isn’t great, and on a 5090 we’re limited to running only the 3-bit version.

On the other hand, Gemma 27B addresses all of these issues except one: writing style. Even the fine-tuned versions we’ve tested still missing emotions and sound too much like a generic “helpful assistant.”

We have millions of chat messages between users and Lamma, and our goal would be to fine-tune Gemma 27B on these responses so it can adopt Finetuned Lamma conversation style while keeping Gemma’s strengths.

Is this something you’d be open to discussing in more detail?

Best regards,
Adam

OddTheGreat

Owner Jan 14

Good time of day.
First of all, thank you for the praise, I am pleased.
Secondly, even if I am open to any discussions, I have to answer you "no". There are several reasons for this, and the simplest one is that I did not fine-tune the models, but only merged them. For now.
I can only advise you to rethink your system prompt used for gemma3, as this greatly affects how emotional the model's responses will be.
Also, I don't want to sound rude, but your message looks suspicious, especially considering your account is empty.
Anyway, thanks again for the positive feedback about the model, have a nice day.

Ful3

Jan 16

Sure fair enough. Thanks for a quick answer .

Ful3 changed discussion status to closed Jan 16

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