Instructions to use mastefan/2025-24679-image-autolguon-predictor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mastefan/2025-24679-image-autolguon-predictor with Transformers:

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

pipe = pipeline("image-text-to-text", model="mastefan/2025-24679-image-autolguon-predictor")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mastefan/2025-24679-image-autolguon-predictor", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use mastefan/2025-24679-image-autolguon-predictor with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mastefan/2025-24679-image-autolguon-predictor"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mastefan/2025-24679-image-autolguon-predictor",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/mastefan/2025-24679-image-autolguon-predictor

SGLang

How to use mastefan/2025-24679-image-autolguon-predictor 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 "mastefan/2025-24679-image-autolguon-predictor" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mastefan/2025-24679-image-autolguon-predictor",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "mastefan/2025-24679-image-autolguon-predictor" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mastefan/2025-24679-image-autolguon-predictor",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use mastefan/2025-24679-image-autolguon-predictor with Docker Model Runner:
```
docker model run hf.co/mastefan/2025-24679-image-autolguon-predictor
```

2025-24679-image-autolguon-predictor

Model description

Purpose: This model to be used for in-class assignments and activity associated with Course 24679 at CMU.

Preprocessing/Augmentation: The preprocessing of this data includes splitting the dataset into train and test, and using autoML to predict whether the image contained in the dataset will have a pen or not. The predictor was multimodal and used a fitting using a 20 minute time limit, in addition to a best_quality present.

Intended uses & limitations

Intented use/limits: The intended use of this dataset is exclusively for classroom and assignment use. Please request permission if you wish to use it elsewhere. Note, accuracy for this model is quite low, due to a low training time for course practice.

Ethical notes: The AI used in this sample is a fairly benign use case handling basic text manipulation. However, please review the environmental impacts of large-scale usage in exchange for implementing the necessary good such technology brings.

AI Usage disclosure: Original code to assist with data augmentation was developed with use of Google Gemini in combination with course material from 24679 at CMU

Training and evaluation data

limitations:

Dataset trained on is a simple image dataset for binary image detection, and has been trained to classify the reccomended column of label. This training model is quite minimal as a result

Downloads last month: -; Downloads are not tracked for this model. How to track

mastefan
/

2025-24679-image-autolguon-predictor

2025-24679-image-autolguon-predictor

Model description

Intended uses & limitations

Training and evaluation data

limitations:

Dataset used to train mastefan/2025-24679-image-autolguon-predictor