Instructions to use Statuo/LemonKunoichiWizardV3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Statuo/LemonKunoichiWizardV3 with Transformers:

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

pipe = pipeline("text-generation", model="Statuo/LemonKunoichiWizardV3")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Statuo/LemonKunoichiWizardV3")
model = AutoModelForCausalLM.from_pretrained("Statuo/LemonKunoichiWizardV3")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Statuo/LemonKunoichiWizardV3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Statuo/LemonKunoichiWizardV3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Statuo/LemonKunoichiWizardV3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Statuo/LemonKunoichiWizardV3

SGLang

How to use Statuo/LemonKunoichiWizardV3 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 "Statuo/LemonKunoichiWizardV3" \
    --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": "Statuo/LemonKunoichiWizardV3",
		"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 "Statuo/LemonKunoichiWizardV3" \
        --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": "Statuo/LemonKunoichiWizardV3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Statuo/LemonKunoichiWizardV3 with Docker Model Runner:
```
docker model run hf.co/Statuo/LemonKunoichiWizardV3
```

Possible to get exl2 quants?

by Shoukupan - opened Nov 29, 2024

Discussion

Shoukupan

Nov 29, 2024

This model has been my favorite so far, I was wondering if it would be possible to get an exl2 version for the speed benefits?

Thanks!

Statuo

Owner Nov 29, 2024

Should already have it. On the model page just below the picture are links to the EXL2 quants.
https://huggingface.co/Statuo/LemonKunoichiWizardv3_4bpw
https://huggingface.co/Statuo/LemonKunoichiWizardv3_6bpw
https://huggingface.co/Statuo/LemonKunoichiWizardv3_8bpw

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