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

Libraries

How to use karlkwon/git-base-pokemon with Transformers:

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

pipe = pipeline("image-text-to-text", model="karlkwon/git-base-pokemon")

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

processor = AutoProcessor.from_pretrained("karlkwon/git-base-pokemon")
model = AutoModelForMultimodalLM.from_pretrained("karlkwon/git-base-pokemon", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use karlkwon/git-base-pokemon with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/karlkwon/git-base-pokemon

SGLang

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

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

git-base-pokemon

Commit History

Nov 13, 2025

18:17
Adding `safetensors` variant of this model⁠

SFconvertbot

Verified signature
04bbbcc

Aug 27, 2023

16:14
Training in progress, step 950

karlkwon

d4a9cc6
16:09
Training in progress, step 650

karlkwon

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16:05
Training in progress, step 350

karlkwon

d22c9f5
16:00
Training in progress, step 50

karlkwon

b2ed401

Jun 16, 2023

22:03
update model card README.md

karlkwon

2e3063b
22:01
End of training

karlkwon

11996ab
21:01
Training in progress, step 50

karlkwon

36102d6
20:17
initial commit

karlkwon

25b6d3c

Commit History

Nov 13, 2025

Adding `safetensors` variant of this model⁠

Aug 27, 2023

Training in progress, step 950

Training in progress, step 650

Training in progress, step 350

Training in progress, step 50

Jun 16, 2023

update model card README.md

End of training

Training in progress, step 50

initial commit