Instructions to use marcderbauer/vice-headlines with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use marcderbauer/vice-headlines with Transformers:

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

pipe = pipeline("text-generation", model="marcderbauer/vice-headlines")

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

tokenizer = AutoTokenizer.from_pretrained("marcderbauer/vice-headlines")
model = AutoModelForCausalLM.from_pretrained("marcderbauer/vice-headlines", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use marcderbauer/vice-headlines with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/marcderbauer/vice-headlines

SGLang

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

Docker Model Runner
How to use marcderbauer/vice-headlines with Docker Model Runner:
```
docker model run hf.co/marcderbauer/vice-headlines
```

vice-headlines

Commit History

Apr 2, 2023

23:14
Adding `safetensors` variant of this model⁠

SFconvertbot

cf4ed1d

Sep 23, 2022

13:08
Upload config.json

marcderbauer

13685b6
13:08
Upload training_args.bin

marcderbauer

9481c26
13:07
Upload trainer_state.json

marcderbauer

e6040b0
13:07
Upload rng_state.pth

marcderbauer

96e99f1
13:06
Upload config.json

marcderbauer

83c307f
13:06
udpate model

marcderbauer

625e269
13:06
update optimizer

marcderbauer

aa579cd
09:08
Update scheduler

marcderbauer

b6a513d
09:00
README v1

marcderbauer

d4c1ae2

Sep 17, 2022

13:10
Upload tokenizer_config.json

marcderbauer

1300be8
13:10
Upload special_tokens_map.json

marcderbauer

29e87e3
13:09
Upload tokenizer.json

marcderbauer

5935297
10:18
Upload . with huggingface_hub (#1)⁠

marcderbauer

14113fb
09:16
initial commit

marcderbauer

e96ffa9

Commit History

Apr 2, 2023

Adding `safetensors` variant of this model⁠

Sep 23, 2022

Upload config.json

Upload training_args.bin

Upload trainer_state.json

Upload rng_state.pth

Upload config.json

udpate model

update optimizer

Update scheduler

README v1

Sep 17, 2022

Upload tokenizer_config.json

Upload special_tokens_map.json

Upload tokenizer.json

Upload . with huggingface_hub (#1)⁠

initial commit