Instructions to use or4cl3ai/SquanchNastyAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use or4cl3ai/SquanchNastyAI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="or4cl3ai/SquanchNastyAI")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("or4cl3ai/SquanchNastyAI", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use or4cl3ai/SquanchNastyAI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "or4cl3ai/SquanchNastyAI" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "or4cl3ai/SquanchNastyAI", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/or4cl3ai/SquanchNastyAI
- SGLang
How to use or4cl3ai/SquanchNastyAI 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 "or4cl3ai/SquanchNastyAI" \ --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": "or4cl3ai/SquanchNastyAI", "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 "or4cl3ai/SquanchNastyAI" \ --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": "or4cl3ai/SquanchNastyAI", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use or4cl3ai/SquanchNastyAI with Docker Model Runner:
docker model run hf.co/or4cl3ai/SquanchNastyAI
Update README.md
What is up with these ai models having no weights and every dataset under the sun on its read me? What kind of scam is this?
its an unfinished project if it was a scam wouldn't i be trying to get something out of it
there is no one else involved just me
when you put those dataset tags on your model it puts the same tag on the dataset page. that there is a model trained on this dataset. which is a lie. this model doesnt exist. it does involve others because of the way huggingface tagging works. im sorry you didnt know that but now you do. i had to change my dataset name because of this so people wouldnt think this model was trained on my dataset. now you see how it affects others