Instructions to use JakeTurner616/Adonalsium-gpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JakeTurner616/Adonalsium-gpt2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="JakeTurner616/Adonalsium-gpt2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("JakeTurner616/Adonalsium-gpt2") model = AutoModelForCausalLM.from_pretrained("JakeTurner616/Adonalsium-gpt2") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use JakeTurner616/Adonalsium-gpt2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "JakeTurner616/Adonalsium-gpt2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "JakeTurner616/Adonalsium-gpt2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/JakeTurner616/Adonalsium-gpt2
- SGLang
How to use JakeTurner616/Adonalsium-gpt2 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 "JakeTurner616/Adonalsium-gpt2" \ --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": "JakeTurner616/Adonalsium-gpt2", "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 "JakeTurner616/Adonalsium-gpt2" \ --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": "JakeTurner616/Adonalsium-gpt2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use JakeTurner616/Adonalsium-gpt2 with Docker Model Runner:
docker model run hf.co/JakeTurner616/Adonalsium-gpt2
Adonalsium-gpt
Basic Information
- Model Name: Adonalsium-gpt2
- Model Type: Text Generation
- Developers: Jake T, Ilijah P
- Contact Information: jake@serverboi.org, Github repo
- Model Data Source: Cosmere series novels by Brandon Sanderson. Dataset and workflows can be found here
- Data Visualization: Cosmere Character Visualization
- Training and Generation Notebook: Google Colab Notebook
Overview
This LLM was trained as an attempt to generate text that mirrors the complex narrative and character interactions of Brandon Sanderson's Cosmere series, aiming to enhance creative storytelling and facilitate academic research in narrative analysis.
Data Source
The model leverages comprehensive datasets derived from the entire Cosmere series, enriched by dynamic visualizations that highlight the complex interplay of relationships and interactions within the Cosmere universe.
Technical Details
- Environment: Google Colab
- Architecture: Adaptations of GPT-2/GPT-3 tailored for Cosmere narratives
- Training Data: Cosmere series
Detailed technical specifics, including architecture choices, hyperparameters, and training methodologies, are documented in the accompanying training and generation notebook.
Access and Usage
The model is accessible for use as detailed in the training and generation notebook, designed to streamline adoption for creative and research endeavors within the Cosmere thematic universe.
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