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

0bf7586

verified ·

1 Parent(s): 2a535b4

End of training

Browse files

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README.md +3 -3
model.safetensors +1 -1
training_args.bin +1 -1

README.md CHANGED Viewed

@@ -15,8 +15,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 6.4307
-- Bleu Score: 0.0009
 ## Model description
@@ -50,7 +50,7 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch  | Step | Validation Loss | Bleu Score |
 |:-------------:|:------:|:----:|:---------------:|:----------:|
-| 7.9533        | 1.7544 | 50   | 6.4307          | 0.0009     |
 ### Framework versions

 This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 6.4119
+- Bleu Score: 0.0018
 ## Model description
 | Training Loss | Epoch  | Step | Validation Loss | Bleu Score |
 |:-------------:|:------:|:----:|:---------------:|:----------:|
+| 7.9411        | 1.7544 | 50   | 6.4119          | 0.0018     |
 ### Framework versions

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