Instructions to use Henk717/spring-dragon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Henk717/spring-dragon with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Henk717/spring-dragon")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Henk717/spring-dragon") model = AutoModelForCausalLM.from_pretrained("Henk717/spring-dragon") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Henk717/spring-dragon with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Henk717/spring-dragon" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Henk717/spring-dragon", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Henk717/spring-dragon
- SGLang
How to use Henk717/spring-dragon 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 "Henk717/spring-dragon" \ --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": "Henk717/spring-dragon", "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 "Henk717/spring-dragon" \ --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": "Henk717/spring-dragon", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Henk717/spring-dragon with Docker Model Runner:
docker model run hf.co/Henk717/spring-dragon
High hopes
As a former Ai dungeon player from 2019 i used to use it A LOT and i do have to say i prefered the old model compared to the new ones from today. I remember when i first played it and it was just the most amazing thing ever. I still remember when they changed the model and the quality of the outputs declined and switched a live service. i still decided to pay for the service after that but after i heard there was a data leak and a few other stuff so i stopped using it and switched to NovelAi when it came out which at the time was better than anything Ai Dungeon was doing. I will definitely download this model and test this.
Let me know if its sufficiently AI Dungeon like (Best results in KoboldAI's UI the model will set the required settings automatically), it was my first attempt at doing this. If its trained to weak it may not be AI Dungeon enough, if its on point topically but not powerful enough i'd have to redo it on a larger model.
I will let you know π