Instructions to use 0Tick/danbooruTagAutocomplete with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use 0Tick/danbooruTagAutocomplete with Transformers:

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

pipe = pipeline("text-generation", model="0Tick/danbooruTagAutocomplete")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("0Tick/danbooruTagAutocomplete")
model = AutoModelForCausalLM.from_pretrained("0Tick/danbooruTagAutocomplete")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use 0Tick/danbooruTagAutocomplete with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "0Tick/danbooruTagAutocomplete"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "0Tick/danbooruTagAutocomplete",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/0Tick/danbooruTagAutocomplete

SGLang

How to use 0Tick/danbooruTagAutocomplete 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 "0Tick/danbooruTagAutocomplete" \
    --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": "0Tick/danbooruTagAutocomplete",
		"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 "0Tick/danbooruTagAutocomplete" \
        --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": "0Tick/danbooruTagAutocomplete",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use 0Tick/danbooruTagAutocomplete with Docker Model Runner:
```
docker model run hf.co/0Tick/danbooruTagAutocomplete
```

0Tick commited on Feb 21, 2023

Commit

569d06f

1 Parent(s): 2de9aca

Update README.md

Browse files

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README.md +1 -1

README.md CHANGED Viewed

@@ -17,7 +17,7 @@ pipeline_tag: text-generation
 ## Model description
 This is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) which is intended to be used with the [promptgen](https://github.com/AUTOMATIC1111/stable-diffusion-webui-promptgen) extension inside the AUTOMATIC1111 WebUI.
-It is trained on the raw tags of danbooru with underscores and spaces
 # Training

 ## Model description
 This is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) which is intended to be used with the [promptgen](https://github.com/AUTOMATIC1111/stable-diffusion-webui-promptgen) extension inside the AUTOMATIC1111 WebUI.
+It is trained on the raw tags of danbooru with underscores and spaces. Only posts with a rating higher than "General" were included in the dataset.
 # Training