Instructions to use MHamdan/model-book-covers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MHamdan/model-book-covers with Transformers:

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

pipe = pipeline("image-text-to-text", model="MHamdan/model-book-covers")

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

tokenizer = AutoTokenizer.from_pretrained("MHamdan/model-book-covers")
model = AutoModelForMultimodalLM.from_pretrained("MHamdan/model-book-covers", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use MHamdan/model-book-covers with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/MHamdan/model-book-covers

SGLang

How to use MHamdan/model-book-covers 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 "MHamdan/model-book-covers" \
    --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": "MHamdan/model-book-covers",
		"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 "MHamdan/model-book-covers" \
        --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": "MHamdan/model-book-covers",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use MHamdan/model-book-covers with Docker Model Runner:
```
docker model run hf.co/MHamdan/model-book-covers
```

model-book-covers

Commit History

Jul 16, 2025

05:22
Adding `safetensors` variant of this model⁠

SFconvertbot

Verified signature
373529b

Sep 27, 2022

20:55
Training in progress, epoch 1

MHamdan

2538352
18:16
Training in progress, epoch 0

MHamdan

28ec66d

Sep 24, 2022

20:56
Training done

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Training done

MHamdan

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20:55
Training in progress, epoch 4

MHamdan

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19:17
Training in progress, epoch 3

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Training in progress, epoch 2

MHamdan

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Training in progress, epoch 1

MHamdan

9ea886a
14:18
Training in progress, epoch 0

MHamdan

bf797d0
14:17
initial commit

MHamdan

721d8c1

Commit History

Jul 16, 2025

Adding `safetensors` variant of this model⁠

Sep 27, 2022

Training in progress, epoch 1

Training in progress, epoch 0

Sep 24, 2022

Training done

Training done

Training in progress, epoch 4

Training in progress, epoch 3

Training in progress, epoch 2

Training in progress, epoch 1

Training in progress, epoch 0

initial commit