Not-For-All-Audiences

Instructions to use KBlueLeaf/DanTagGen-gamma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use KBlueLeaf/DanTagGen-gamma with Transformers:

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

pipe = pipeline("text-generation", model="KBlueLeaf/DanTagGen-gamma")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("KBlueLeaf/DanTagGen-gamma")
model = AutoModelForCausalLM.from_pretrained("KBlueLeaf/DanTagGen-gamma", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use KBlueLeaf/DanTagGen-gamma with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf KBlueLeaf/DanTagGen-gamma:Q6_K
# Run inference directly in the terminal:
llama cli -hf KBlueLeaf/DanTagGen-gamma:Q6_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf KBlueLeaf/DanTagGen-gamma:Q6_K
# Run inference directly in the terminal:
llama cli -hf KBlueLeaf/DanTagGen-gamma:Q6_K

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf KBlueLeaf/DanTagGen-gamma:Q6_K
# Run inference directly in the terminal:
./llama-cli -hf KBlueLeaf/DanTagGen-gamma:Q6_K

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf KBlueLeaf/DanTagGen-gamma:Q6_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf KBlueLeaf/DanTagGen-gamma:Q6_K

Use Docker

docker model run hf.co/KBlueLeaf/DanTagGen-gamma:Q6_K

LM Studio
Jan

vLLM

How to use KBlueLeaf/DanTagGen-gamma with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/KBlueLeaf/DanTagGen-gamma:Q6_K

SGLang

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

Ollama
How to use KBlueLeaf/DanTagGen-gamma with Ollama:
```
ollama run hf.co/KBlueLeaf/DanTagGen-gamma:Q6_K
```
Unsloth Desktop
Docker Model Runner
How to use KBlueLeaf/DanTagGen-gamma with Docker Model Runner:
```
docker model run hf.co/KBlueLeaf/DanTagGen-gamma:Q6_K
```

Lemonade

How to use KBlueLeaf/DanTagGen-gamma with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull KBlueLeaf/DanTagGen-gamma:Q6_K

Run and chat with the model

lemonade run user.DanTagGen-gamma-Q6_K

List all available models

lemonade list

Atomic Chat
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

DanTagGen - gamma

DanTagGen(Danbooru Tag Generator) is inspired from p1atdev's dart project. But with different arch, dataset, format and different training strategy.

Difference between versions

alpha: pretrain on 2M dataset, smaller batch size. Limited ability
beta: pretrain on 5.3M dataset, larger batch size. More stable, better ability with only a few information provided.
gamma: finetuned from beta, with 3.6M dataset (union of all posts after id 5,000,000 and top25% fav count posts)

Model arch

This version of DTG is trained from scratch with 400M param LLaMA arch.(In my personal preference I will call it NanoLLaMA) Since it is llama arch. Theoritically it should be able to be used in any LLaMA inference interface.

This repo also provided converted FP16 gguf model and quantized 8bit/6bit gguf models. Basically it is recommended to use llama.cpp or llama-cpp-python to run this model. Which will be very fast.

Format

prompt = f"""
rating: {rating or '<|empty|>'}
artist: {artist.strip() or '<|empty|>'}
characters: {characters.strip() or '<|empty|>'}
copyrights: {copyrights.strip() or '<|empty|>'}
aspect ratio: {f"{aspect_ratio:.1f}" or '<|empty|>'}
target: {'<|' + target + '|>' if target else '<|long|>'}
general: {", ".join(special_tags)}, {general.strip().strip(",")}<|input_end|>
"""

for example:

rating: safe
artist: <|empty|>
characters: <|empty|>
copyrights: <|empty|>
aspect ratio: 1.0
target: <|short|>
general: 1girl, solo, dragon girl, dragon horns, dragon tail<|input_end|>

And you may get something like:

rating: safe
artist: <|empty|>
characters: <|empty|>
copyrights: <|empty|>
aspect ratio: 1.0
target: <|short|>
general: 1girl, solo, dragon girl, dragon horns, dragon tail<|input_end|>open mouth, red eyes, long hair, pointy ears, tail, black hair, chinese clothes, simple background, dragon, hair between eyes, horns, china dress, dress, looking at viewer, breasts