Instructions to use Statuo/LemonWizardv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Statuo/LemonWizardv3 with Transformers:

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

pipe = pipeline("text-generation", model="Statuo/LemonWizardv3")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Statuo/LemonWizardv3")
model = AutoModelForCausalLM.from_pretrained("Statuo/LemonWizardv3")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Statuo/LemonWizardv3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Statuo/LemonWizardv3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Statuo/LemonWizardv3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Statuo/LemonWizardv3

SGLang

How to use Statuo/LemonWizardv3 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/LemonWizardv3" \
    --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/LemonWizardv3",
		"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/LemonWizardv3" \
        --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/LemonWizardv3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Statuo/LemonWizardv3 with Docker Model Runner:
```
docker model run hf.co/Statuo/LemonWizardv3
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Intent

The intent was to combine the excellent LemonadeRP-4.5.3 with WizardLM-2 in order to produce more effective uncensored content. While WizardLM-2 wouldn't balk at uncensored content, it would still falter in actually producing it whereas LemonadeRP didn't have this issue. The results are pretty good imo. There's a problem that if your response length is too long it will start to speak for the user but those usually disappear on swipes.

I had originally not intended to release this model and instead keep it private. It's my first foray into doing merges at all and I didn't want to release a subpar model. However, after encouragement I've decided to unprivate it. Hope you all get some enjoyment out of it.

Prompt - Alpaca

Using the Alpaca prompt seems to get good results.

Context Size - 8192

Haven't tested beyond this. Usual rule of thumb is that once you get up to 12k your responses tend to become less coherent and 16k is where things just devolve completely.

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: Replete-AI/WizardLM-2-7b
  - model: KatyTheCutie/LemonadeRP-4.5.3
merge_method: slerp
base_model: KatyTheCutie/LemonadeRP-4.5.3
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers

Downloads last month: 3

Safetensors

Model size

7B params

Tensor type

BF16

Model tree for Statuo/LemonWizardv3

Base model

NeverSleep/Noromaid-7B-0.4-DPO

Finetuned

KatyTheCutie/LemonadeRP-4.5.3

Finetuned

(4)

this model

Quantizations

1 model