Text Generation
Transformers
TensorBoard
Safetensors
gpt_neox
Generated from Trainer
text-generation-inference
Instructions to use ij5/arstyle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ij5/arstyle with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ij5/arstyle")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ij5/arstyle") model = AutoModelForCausalLM.from_pretrained("ij5/arstyle", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ij5/arstyle with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ij5/arstyle" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ij5/arstyle", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ij5/arstyle
- SGLang
How to use ij5/arstyle 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 "ij5/arstyle" \ --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": "ij5/arstyle", "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 "ij5/arstyle" \ --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": "ij5/arstyle", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ij5/arstyle with Docker Model Runner:
docker model run hf.co/ij5/arstyle
Download model.safetensors from ij5/arstyle: direct link, hf CLI and curl.
- Browser
- Download file 2.66 GB
-
https://huggingface.co/ij5/arstyle/resolve/main/model.safetensors
- Command line
-
hf download hf://ij5/arstyle/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ij5/arstyle/resolve/main/model.safetensors
2.66 GB
- Xet hash:
- 89a4a7e1e5f164adb5446ab001448137d3d2d69a4f4b93937c58c3b85c0e2848
- Size of remote file:
- 2.66 GB
- SHA256:
- 7e336bb4a06d0a02c2d4455fb7bebab8c37acbdc51e1cadc339db7b48a999193
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