Instructions to use Undi95/Llama-3-LewdPlay-8B-evo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Undi95/Llama-3-LewdPlay-8B-evo with Transformers:

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

pipe = pipeline("text-generation", model="Undi95/Llama-3-LewdPlay-8B-evo")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Undi95/Llama-3-LewdPlay-8B-evo")
model = AutoModelForCausalLM.from_pretrained("Undi95/Llama-3-LewdPlay-8B-evo")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Undi95/Llama-3-LewdPlay-8B-evo with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Undi95/Llama-3-LewdPlay-8B-evo"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Undi95/Llama-3-LewdPlay-8B-evo",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Undi95/Llama-3-LewdPlay-8B-evo

SGLang

How to use Undi95/Llama-3-LewdPlay-8B-evo 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 "Undi95/Llama-3-LewdPlay-8B-evo" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Undi95/Llama-3-LewdPlay-8B-evo",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "Undi95/Llama-3-LewdPlay-8B-evo" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Undi95/Llama-3-LewdPlay-8B-evo",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Undi95/Llama-3-LewdPlay-8B-evo with Docker Model Runner:
```
docker model run hf.co/Undi95/Llama-3-LewdPlay-8B-evo
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

LewdPlay-8B

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

The new EVOLVE merge method was used (on MMLU specifically), see below for more information!

Unholy was used for uncensoring, Roleplay Llama 3 for the DPO train he got on top, and LewdPlay for the... lewd side.

Prompt template: Llama3

<|begin_of_text|><|start_header_id|>system<|end_header_id|>

{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>

{input}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

{output}<|eot_id|>

Merge Details

Merge Method

This model was merged using the DARE TIES merge method using ./mergekit/input_models/Roleplay-Llama-3-8B_213413727 as a base.

Models Merged

The following models were included in the merge:

./mergekit/input_models/Llama-3-Unholy-8B-e4_1440388923
./mergekit/input_models/Llama-3-LewdPlay-8B-e3_2981937066

Configuration

The following YAML configuration was used to produce this model:

base_model: ./mergekit/input_models/Roleplay-Llama-3-8B_213413727
dtype: bfloat16
merge_method: dare_ties
parameters:
  int8_mask: 1.0
  normalize: 0.0
slices:
- sources:
  - layer_range: [0, 4]
    model: ./mergekit/input_models/Llama-3-LewdPlay-8B-e3_2981937066
    parameters:
      density: 1.0
      weight: 0.6861808716092435
  - layer_range: [0, 4]
    model: ./mergekit/input_models/Llama-3-Unholy-8B-e4_1440388923
    parameters:
      density: 0.6628290134113985
      weight: 0.5815923052193855
  - layer_range: [0, 4]
    model: ./mergekit/input_models/Roleplay-Llama-3-8B_213413727
    parameters:
      density: 1.0
      weight: 0.5113886163963061
- sources:
  - layer_range: [4, 8]
    model: ./mergekit/input_models/Llama-3-LewdPlay-8B-e3_2981937066
    parameters:
      density: 0.892655547455918
      weight: 0.038732602391021484
  - layer_range: [4, 8]
    model: ./mergekit/input_models/Llama-3-Unholy-8B-e4_1440388923
    parameters:
      density: 1.0
      weight: 0.1982145486303527
  - layer_range: [4, 8]
    model: ./mergekit/input_models/Roleplay-Llama-3-8B_213413727
    parameters:
      density: 1.0
      weight: 0.6843011350690802
- sources:
  - layer_range: [8, 12]
    model: ./mergekit/input_models/Llama-3-LewdPlay-8B-e3_2981937066
    parameters:
      density: 0.7817511027396784
      weight: 0.13053333213489704
  - layer_range: [8, 12]
    model: ./mergekit/input_models/Llama-3-Unholy-8B-e4_1440388923
    parameters:
      density: 0.6963703515864826
      weight: 0.20525481492667985
  - layer_range: [8, 12]
    model: ./mergekit/input_models/Roleplay-Llama-3-8B_213413727
    parameters:
      density: 0.6983086326765777
      weight: 0.5843953969574106
- sources:
  - layer_range: [12, 16]
    model: ./mergekit/input_models/Llama-3-LewdPlay-8B-e3_2981937066
    parameters:
      density: 0.9632895768462915
      weight: 0.2101146706607748
  - layer_range: [12, 16]
    model: ./mergekit/input_models/Llama-3-Unholy-8B-e4_1440388923
    parameters:
      density: 0.597557434542081
      weight: 0.6728172621848589
  - layer_range: [12, 16]
    model: ./mergekit/input_models/Roleplay-Llama-3-8B_213413727
    parameters:
      density: 0.756263557607837
      weight: 0.2581423726361908
- sources:
  - layer_range: [16, 20]
    model: ./mergekit/input_models/Llama-3-LewdPlay-8B-e3_2981937066
    parameters:
      density: 1.0
      weight: 0.2116035543552448
  - layer_range: [16, 20]
    model: ./mergekit/input_models/Llama-3-Unholy-8B-e4_1440388923
    parameters:
      density: 1.0
      weight: 0.22654226422958418
  - layer_range: [16, 20]
    model: ./mergekit/input_models/Roleplay-Llama-3-8B_213413727
    parameters:
      density: 0.8925914810507647
      weight: 0.42243766315440867
- sources:
  - layer_range: [20, 24]
    model: ./mergekit/input_models/Llama-3-LewdPlay-8B-e3_2981937066
    parameters:
      density: 0.7697608089825734
      weight: 0.1535118632140203
  - layer_range: [20, 24]
    model: ./mergekit/input_models/Llama-3-Unholy-8B-e4_1440388923
    parameters:
      density: 0.9886758076773643
      weight: 0.3305040603868546
  - layer_range: [20, 24]
    model: ./mergekit/input_models/Roleplay-Llama-3-8B_213413727
    parameters:
      density: 1.0
      weight: 0.40670083428654535
- sources:
  - layer_range: [24, 28]
    model: ./mergekit/input_models/Llama-3-LewdPlay-8B-e3_2981937066
    parameters:
      density: 1.0
      weight: 0.4542810478500622
  - layer_range: [24, 28]
    model: ./mergekit/input_models/Llama-3-Unholy-8B-e4_1440388923
    parameters:
      density: 0.8330662483310117
      weight: 0.2587495367324508
  - layer_range: [24, 28]
    model: ./mergekit/input_models/Roleplay-Llama-3-8B_213413727
    parameters:
      density: 0.9845313983551542
      weight: 0.40378452705975915
- sources:
  - layer_range: [28, 32]
    model: ./mergekit/input_models/Llama-3-LewdPlay-8B-e3_2981937066
    parameters:
      density: 1.0
      weight: 0.2951962192288415
  - layer_range: [28, 32]
    model: ./mergekit/input_models/Llama-3-Unholy-8B-e4_1440388923
    parameters:
      density: 0.960315594933433
      weight: 0.13142971773782525
  - layer_range: [28, 32]
    model: ./mergekit/input_models/Roleplay-Llama-3-8B_213413727
    parameters:
      density: 1.0
      weight: 0.30838472094518804