Instructions to use minwook/git-base-cartoon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use minwook/git-base-cartoon with Transformers:

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

pipe = pipeline("image-text-to-text", model="minwook/git-base-cartoon")

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("minwook/git-base-cartoon")
model = AutoModelForImageTextToText.from_pretrained("minwook/git-base-cartoon")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use minwook/git-base-cartoon with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/minwook/git-base-cartoon

SGLang

How to use minwook/git-base-cartoon 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 "minwook/git-base-cartoon" \
    --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": "minwook/git-base-cartoon",
		"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 "minwook/git-base-cartoon" \
        --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": "minwook/git-base-cartoon",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use minwook/git-base-cartoon with Docker Model Runner:
```
docker model run hf.co/minwook/git-base-cartoon
```

minwook commited on Aug 2, 2024

Commit

8564aac

verified ·

1 Parent(s): c8616fa

Training in progress, step 50

Browse files

Files changed (3) hide show

model.safetensors +1 -1
runs/Aug02_04-43-24_0d101aa3107a/events.out.tfevents.1722573847.0d101aa3107a.7792.0 +3 -0
training_args.bin +1 -1

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5f7b43496ceed0567128be2b1c851aaba83023d44ba8a359f406098a182f94f1
 size 706516040

 version https://git-lfs.github.com/spec/v1
+oid sha256:581c6a23b28393c99204ea0422c925c59515bf0859eed9911f35742fd00dd627
 size 706516040

runs/Aug02_04-43-24_0d101aa3107a/events.out.tfevents.1722573847.0d101aa3107a.7792.0 ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:c8ecaf8a2f2e14fb1ce5872437d9618c2ff0922a328bdd3c3cf2529e0bed1e93
+size 5582

training_args.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:43472a8f59fba02a8480c8314df4e36d0ef7dc0ec040bb7945a442bdc1619182
 size 5112

 version https://git-lfs.github.com/spec/v1
+oid sha256:eea547961dbf9817c7f9f63c35944974b8b6aa74c96041955bf48db69d2fee73
 size 5112