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
```

Librarian Bot: Add base_model information to model

by librarian-bot - opened Sep 11, 2023

base: refs/heads/main

←

from: refs/pr/3

Discussion Files changed

-7

Files changed (1) hide show

README.md +8 -7

README.md CHANGED Viewed

@@ -1,19 +1,20 @@
 ---
 license: mit
 tags:
 - generated_from_trainer
 metrics:
 - accuracy
 model-index:
 - name: danbooruTagAutocomplete
   results: []
-co2_eq_emissions: 100
-language:
-- en
-library_name: transformers
-pipeline_tag: text-generation
-datasets:
-- 0Tick/Danbooru-Random-Posts-Scrape
 ---
 ## Model description

 ---
+language:
+- en
 license: mit
+library_name: transformers
 tags:
 - generated_from_trainer
+datasets:
+- 0Tick/Danbooru-Random-Posts-Scrape
 metrics:
 - accuracy
+co2_eq_emissions: 100
+pipeline_tag: text-generation
+base_model: distilgpt2
 model-index:
 - name: danbooruTagAutocomplete
   results: []
 ---
 ## Model description