Instructions to use FINAL-Bench/Darwin-180B-RSI-R3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FINAL-Bench/Darwin-180B-RSI-R3 with Transformers:

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

pipe = pipeline("image-text-to-text", model="FINAL-Bench/Darwin-180B-RSI-R3")
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)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("FINAL-Bench/Darwin-180B-RSI-R3")
model = AutoModelForMultimodalLM.from_pretrained("FINAL-Bench/Darwin-180B-RSI-R3", 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=256)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FINAL-Bench/Darwin-180B-RSI-R3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FINAL-Bench/Darwin-180B-RSI-R3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FINAL-Bench/Darwin-180B-RSI-R3",
		"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/FINAL-Bench/Darwin-180B-RSI-R3

SGLang

How to use FINAL-Bench/Darwin-180B-RSI-R3 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 "FINAL-Bench/Darwin-180B-RSI-R3" \
    --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": "FINAL-Bench/Darwin-180B-RSI-R3",
		"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 "FINAL-Bench/Darwin-180B-RSI-R3" \
        --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": "FINAL-Bench/Darwin-180B-RSI-R3",
		"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 FINAL-Bench/Darwin-180B-RSI-R3 with Docker Model Runner:
```
docker model run hf.co/FINAL-Bench/Darwin-180B-RSI-R3
```

Darwin-180B-RSI-R3

Commit History

Nov 13 2 days ago

02:43
Point Darwin Family paper link to the Hugging Face paper page

SeaWolf-AI

Verified signature
f029e80

Nov 7 8 days ago

04:26
Model card: SuperCLUE Nov 2026 result (#1 open-weight, #2 overall in math and science reasoning)

SeaWolf-AI

Verified signature
32a97e3

Oct 29 17 days ago

14:13
Add ArguAna nDCG@10 83.83 (embedding + Darwin rerank)

SeaWolf-AI

Verified signature
3e61b93

Oct 5

23:05
card: ten #1s in the RSI line (MDPBench by R1)

SeaWolf-AI

Verified signature
1549515
07:30
card: nine #1s in the RSI line (IFStruct by R1)

SeaWolf-AI

Verified signature
102dd91
04:00
card: inherit Darwin-180B-RSI card; eight #1s in the RSI line (ExtractBench by R3, seven by R1)

SeaWolf-AI

Verified signature
5ee02b9
02:10
card: drop base_model metadata (lineage stays in the card body)

SeaWolf-AI

Verified signature
9259257
02:05
ExtractBench 90.29 (thinking off, single run) + card: leaderboard status

SeaWolf-AI

Verified signature
57259a5
01:47
Add ExtractBench and EvasionBench eval results

SeaWolf-AI

Verified signature
fef2e66

Oct 2

06:17
card: link POCKET-Darwin-180B-GGUF (4-bit, laptop / CPU-only)

SeaWolf-AI

Verified signature
ff75693

Oct 1

04:51
Add files using upload-large-folder tool

SeaWolf-AI

Verified signature
a43d65f
04:51
Add files using upload-large-folder tool

SeaWolf-AI

Verified signature
e9f7db5
04:51
Add files using upload-large-folder tool

SeaWolf-AI

Verified signature
25d3fde
04:41
Darwin-180B-RSI-R3: config and card

SeaWolf-AI

Verified signature
8cc244b
04:41
initial commit

SeaWolf-AI

Verified signature
330cfa5

Commit History

Nov 13 2 days ago

Point Darwin Family paper link to the Hugging Face paper page

Nov 7 8 days ago

Model card: SuperCLUE Nov 2026 result (#1 open-weight, #2 overall in math and science reasoning)

Oct 29 17 days ago

Add ArguAna nDCG@10 83.83 (embedding + Darwin rerank)

Oct 5

card: ten #1s in the RSI line (MDPBench by R1)

card: nine #1s in the RSI line (IFStruct by R1)

card: inherit Darwin-180B-RSI card; eight #1s in the RSI line (ExtractBench by R3, seven by R1)

card: drop base_model metadata (lineage stays in the card body)

ExtractBench 90.29 (thinking off, single run) + card: leaderboard status

Add ExtractBench and EvasionBench eval results

Oct 2

card: link POCKET-Darwin-180B-GGUF (4-bit, laptop / CPU-only)

Oct 1

Add files using upload-large-folder tool

Add files using upload-large-folder tool

Add files using upload-large-folder tool

Darwin-180B-RSI-R3: config and card

initial commit