Instructions to use Siddu0406/article-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Siddu0406/article-generator with Transformers:

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

pipe = pipeline("text-generation", model="Siddu0406/article-generator")

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

tokenizer = AutoTokenizer.from_pretrained("Siddu0406/article-generator")
model = AutoModelForCausalLM.from_pretrained("Siddu0406/article-generator", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Siddu0406/article-generator with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Siddu0406/article-generator"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Siddu0406/article-generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Siddu0406/article-generator

SGLang

How to use Siddu0406/article-generator 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 "Siddu0406/article-generator" \
    --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": "Siddu0406/article-generator",
		"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 "Siddu0406/article-generator" \
        --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": "Siddu0406/article-generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Siddu0406/article-generator with Docker Model Runner:
```
docker model run hf.co/Siddu0406/article-generator
```

article-generator

Commit History

Sep 11, 2023

15:01
Librarian Bot: Add base_model information to model⁠

librarian-bot

4f22b38

Dec 26, 2022

08:26
Upload tokenizer

Siddu0406

1c448ba
08:26
End of training

Siddu0406

5510d7e
08:26
update model card README.md

Siddu0406

cdcd779
08:19
Model save

Siddu0406

aae88c2
07:58
initial commit

Siddu0406

93df63d

Commit History

Sep 11, 2023

Librarian Bot: Add base_model information to model⁠

Dec 26, 2022

Upload tokenizer

End of training

update model card README.md

Model save

initial commit