Instructions to use ncauchi1/general_questions_model_v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ncauchi1/general_questions_model_v0 with Transformers:

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

pipe = pipeline("image-text-to-text", model="ncauchi1/general_questions_model_v0")
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("ncauchi1/general_questions_model_v0")
model = AutoModelForMultimodalLM.from_pretrained("ncauchi1/general_questions_model_v0")
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 ncauchi1/general_questions_model_v0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ncauchi1/general_questions_model_v0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ncauchi1/general_questions_model_v0",
		"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/ncauchi1/general_questions_model_v0

SGLang

How to use ncauchi1/general_questions_model_v0 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 "ncauchi1/general_questions_model_v0" \
    --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": "ncauchi1/general_questions_model_v0",
		"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 "ncauchi1/general_questions_model_v0" \
        --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": "ncauchi1/general_questions_model_v0",
		"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 ncauchi1/general_questions_model_v0 with Docker Model Runner:
```
docker model run hf.co/ncauchi1/general_questions_model_v0
```

Model Card for Model ID

Inital version of VLLM fine tuned to answer general questions about cyclic voltammographs. Evaluated on bxw315-umd/general-cv-questions

Model Details

Training Details

Trained on ncauchi1/general_questions_dataset with 1k samples. Logs found here: [https://wandb.ai/ncauchi-university-of-maryland/huggingface/runs/491q4fd5/logs]

Dataset consists multiple choice questions and reasoning generated with openAI API from templates. Graphs are generated from raw data gathered by me, consisting of CV's of Ferrocene and Tryptophan in PBS with concentrations of 0uM, 100uM and 200uM.

Evaluation

31.6% ± 7.5 Evaluation done on bxw315-umd/general-cv-questions, with an 11.7% increase in performance over base model

Downloads last month: 1

Safetensors

Model size

4B params

Tensor type

BF16

Model tree for ncauchi1/general_questions_model_v0

Base model

Qwen/Qwen2.5-VL-3B-Instruct

Finetuned

(793)

this model

Dataset used to train ncauchi1/general_questions_model_v0

Collection including ncauchi1/general_questions_model_v0

General CV

Collection

Model and datasets used to train general_cv_questions model • 20 items • Updated Aug 12, 2025