Instructions to use IQuestLab/Fleming-VL-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IQuestLab/Fleming-VL-8B with Transformers:

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

pipe = pipeline("image-text-to-text", model="IQuestLab/Fleming-VL-8B", 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 AutoModel
model = AutoModel.from_pretrained("IQuestLab/Fleming-VL-8B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use IQuestLab/Fleming-VL-8B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IQuestLab/Fleming-VL-8B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IQuestLab/Fleming-VL-8B",
		"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/IQuestLab/Fleming-VL-8B

SGLang

How to use IQuestLab/Fleming-VL-8B 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 "IQuestLab/Fleming-VL-8B" \
    --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": "IQuestLab/Fleming-VL-8B",
		"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 "IQuestLab/Fleming-VL-8B" \
        --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": "IQuestLab/Fleming-VL-8B",
		"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 IQuestLab/Fleming-VL-8B with Docker Model Runner:
```
docker model run hf.co/IQuestLab/Fleming-VL-8B
```

thinksoso commited on Nov 11, 2025

Commit

6ca089f

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1 Parent(s): d75a39b

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@@ -1,8 +1,19 @@
 ---
 library_name: transformers
 license: apache-2.0
-license_link: https://huggingface.co/UbiquantAI/Fleming-R1-32B/blob/main/LICENSE
-pipeline_tag: text-generation
 ---
 # Fleming-VL-8B
@@ -628,14 +639,12 @@ In medical scenarios, results must be reviewed and approved by qualified profess
 ## 📚 Citation
-```bibtex
-@misc{flemingr1,
-      title={Fleming-R1: Toward Expert-Level Medical Reasoning via Reinforcement Learning},
-      author={Chi Liu and Derek Li and Yan Shu and Robin Chen and Derek Duan and Teng Fang and Bryan Dai},
       year={2025},
-      eprint={2509.15279},
       archivePrefix={arXiv},
-      primaryClass={cs.LG},
-      url={https://arxiv.org/abs/2509.15279},
 }
-```

 ---
 library_name: transformers
 license: apache-2.0
+license_link: https://huggingface.co/UbiquantAI/Fleming-VL-8B/blob/main/LICENSE
+pipeline_tag: image-text-to-text
+tags:
+  - medical
+  - multimodal
+  - report generation
+  - radiology
+  - clinical-reasoning
+  - MRI
+  - CT
+  - Histopathology
+  - X-ray
+  - Fundus
 ---
 # Fleming-VL-8B
 ## 📚 Citation
+@misc{shu2025flemingvluniversalmedicalvisual,
+      title={Fleming-VL: Towards Universal Medical Visual Reasoning with Multimodal LLMs},
+      author={Yan Shu and Chi Liu and Robin Chen and Derek Li and Bryan Dai},
       year={2025},
+      eprint={2511.00916},
       archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2511.00916},
 }