Instructions to use review-artifacts/nsdl-7b-rl-locus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use review-artifacts/nsdl-7b-rl-locus with Transformers:

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

pipe = pipeline("image-text-to-text", model="review-artifacts/nsdl-7b-rl-locus")
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("review-artifacts/nsdl-7b-rl-locus")
model = AutoModelForMultimodalLM.from_pretrained("review-artifacts/nsdl-7b-rl-locus", 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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use review-artifacts/nsdl-7b-rl-locus with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "review-artifacts/nsdl-7b-rl-locus"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "review-artifacts/nsdl-7b-rl-locus",
		"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/review-artifacts/nsdl-7b-rl-locus

SGLang

How to use review-artifacts/nsdl-7b-rl-locus 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 "review-artifacts/nsdl-7b-rl-locus" \
    --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": "review-artifacts/nsdl-7b-rl-locus",
		"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 "review-artifacts/nsdl-7b-rl-locus" \
        --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": "review-artifacts/nsdl-7b-rl-locus",
		"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 review-artifacts/nsdl-7b-rl-locus with Docker Model Runner:
```
docker model run hf.co/review-artifacts/nsdl-7b-rl-locus
```

NSDL 7B (SFT + RL), LOCUS: anonymized checkpoint for double-anonymous review

Row "Table 2: NSDL 7B (SFT + RL); Fig. 3" of the submission. Weights are stored in bfloat16, the dtype the evaluation loader uses. Load and run with the code in the anonymized repository linked from the paper (nsdl/ + scripts/eval_lnsdl_agentic_viki_l2.py); evaluation flags are in that repository's README. Step-30 checkpoint of the RL run initialised from the NSDL 7B (SFT) LOCUS checkpoint (scripts/rl_final_setting.sh). Provided for peer review only; do not redistribute during review. Author, affiliation and citation information is intentionally omitted.

File	Bytes	sha256
`added_tokens.json`	605	`58b54bbe36fc752f79a24a271ef66a0a0830054b4dfad94bde757d851968060b`
`chat_template.json`	1049	`94174d7176c52a7192f96fc34eb2cf23c7c2059d63cdbfadca1586ba89731fb7`
`config.json`	1541	`ccba9eb5596f73369f80d46f87b9725053c0e9abe4f09ccbef3b945be9a5a71e`
`generation_config.json`	260	`90e92cbc8634d6f5b1cb1ae58a3c48724a1ce1f11f8b7aecb5b9b3fd5d5a06bf`
`merges.txt`	1671853	`8831e4f1a044471340f7c0a83d7bd71306a5b867e95fd870f74d0c5308a904d5`
`model-00001-of-00004.safetensors`	5344827256	`f7d78ca2fca6902c22f2567818941cdb805dafb0dcda0072d7b2cde51274721f`
`model-00002-of-00004.safetensors`	4544503872	`a7934705cbbd58d521ee0407971ba33c658b32302cfc0a6d1ba8a5b850ac0cc8`
`model-00003-of-00004.safetensors`	5362477296	`fbd4d4941f9f95e49496acbe89093dcad4c904531779615be4429b6c9c140b4f`
`model-00004-of-00004.safetensors`	1332606112	`f50334aef9b3a86a47175bf19597e9569ce4b9999e9b4c7104c0d685cd4b8dcb`
`model.safetensors.index.json`	57618	`52ff41850df57394c9bebaa04c6ee9377ccedb2981b7dd1a4eb6d9995b83354d`
`preprocessor_config.json`	571	`10244222141516cc6ac28c41435d5ced7db23d352ce67ae588d5b248ccbc0b2f`
`special_tokens_map.json`	613	`76862e765266b85aa9459767e33cbaf13970f327a0e88d1c65846c2ddd3a1ecd`
`tokenizer.json`	11421995	`33624f49f1034c4f5d92e3ec47ccdf80ccd02caf1eb1d769872ba7fb1e5be112`
`tokenizer_config.json`	5885	`51de45007c92099bcdd5a29b88fd0ee8766f1b3eba601aaed0edb1e42a63828a`
`vocab.json`	2776833	`ca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910`

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Safetensors

Model size

8B params

Tensor type

BF16

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