Instructions to use GoofyLM/N2.3-Eye-1.3B-DEV with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use GoofyLM/N2.3-Eye-1.3B-DEV with Transformers:

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

pipe = pipeline("image-text-to-text", model="GoofyLM/N2.3-Eye-1.3B-DEV", trust_remote_code=True)
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 AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("GoofyLM/N2.3-Eye-1.3B-DEV", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("GoofyLM/N2.3-Eye-1.3B-DEV", trust_remote_code=True)
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 = 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 GoofyLM/N2.3-Eye-1.3B-DEV with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "GoofyLM/N2.3-Eye-1.3B-DEV"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "GoofyLM/N2.3-Eye-1.3B-DEV",
		"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/GoofyLM/N2.3-Eye-1.3B-DEV

SGLang

How to use GoofyLM/N2.3-Eye-1.3B-DEV 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 "GoofyLM/N2.3-Eye-1.3B-DEV" \
    --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": "GoofyLM/N2.3-Eye-1.3B-DEV",
		"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 "GoofyLM/N2.3-Eye-1.3B-DEV" \
        --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": "GoofyLM/N2.3-Eye-1.3B-DEV",
		"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 GoofyLM/N2.3-Eye-1.3B-DEV with Docker Model Runner:
```
docker model run hf.co/GoofyLM/N2.3-Eye-1.3B-DEV
```

FlameF0X commited on Aug 7, 2025

Commit

4f7c22a

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1 Parent(s): 8168c7d

Create config.json

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config.json +42 -0

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	@@ -0,0 +1,42 @@

+{
+  "model_type": "llama",
+  "architectures": ["MultimodalLFM2Model"],
+  "_name_or_path": "GoofyLM/N2.2-Eye-1.3B",
+  "auto_map": {
+    "AutoModelForCausalLM": "modeling_n2_eye.MultimodalLFM2Model",
+    "AutoConfig": "modeling_n2_eye.MultimodalLFM2Config"
+  },
+  "lfm2_model_name": "LiquidAI/LFM2-1.2B",
+  "clip_model_name": "google/siglip2-so400m-patch14-384",
+  "vision_projection_dim": 512,
+  "language_model_config": {
+    "model_type": "lfm2",
+    "hidden_size": 1536,
+    "vocab_size": 50257,
+    "max_position_embeddings": 2048
+  },
+  "vision_encoder_config": {
+    "model_type": "clip_vision_model",
+    "hidden_size": 768
+  },
+  "projection_config": {
+    "vision_hidden_size": 768,
+    "vision_projection_dim": 512,
+    "language_hidden_size": 1536,
+    "dropout": 0.1
+  },
+  "image_token": "<image>",
+  "max_length": 2048,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.46.0",
+  "use_cache": true,
+  "chat_template": "{% set system_message = 'You are a helpful assistant trained by Liquid AI. You can see and understand images.' %}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% endif %}<|im_start|>system\n{{ system_message }}<|im_end|>\n<image>\n{% for message in loop_messages %}<|im_start|>{{ message['role'] }}\n{{ message['content'] }}<|im_end|>\n{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}"
+}