Instructions to use LogicalLion/whiterabbitneo-8b-v1-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use LogicalLion/whiterabbitneo-8b-v1-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="LogicalLion/whiterabbitneo-8b-v1-gguf", filename="whiterabbitneo.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use LogicalLion/whiterabbitneo-8b-v1-gguf with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf LogicalLion/whiterabbitneo-8b-v1-gguf # Run inference directly in the terminal: llama cli -hf LogicalLion/whiterabbitneo-8b-v1-gguf
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf LogicalLion/whiterabbitneo-8b-v1-gguf # Run inference directly in the terminal: llama cli -hf LogicalLion/whiterabbitneo-8b-v1-gguf
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf LogicalLion/whiterabbitneo-8b-v1-gguf # Run inference directly in the terminal: ./llama-cli -hf LogicalLion/whiterabbitneo-8b-v1-gguf
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf LogicalLion/whiterabbitneo-8b-v1-gguf # Run inference directly in the terminal: ./build/bin/llama-cli -hf LogicalLion/whiterabbitneo-8b-v1-gguf
Use Docker
docker model run hf.co/LogicalLion/whiterabbitneo-8b-v1-gguf
- LM Studio
- Jan
- vLLM
How to use LogicalLion/whiterabbitneo-8b-v1-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LogicalLion/whiterabbitneo-8b-v1-gguf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LogicalLion/whiterabbitneo-8b-v1-gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/LogicalLion/whiterabbitneo-8b-v1-gguf
- Ollama
How to use LogicalLion/whiterabbitneo-8b-v1-gguf with Ollama:
ollama run hf.co/LogicalLion/whiterabbitneo-8b-v1-gguf
- Unsloth Studio
How to use LogicalLion/whiterabbitneo-8b-v1-gguf with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for LogicalLion/whiterabbitneo-8b-v1-gguf to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for LogicalLion/whiterabbitneo-8b-v1-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for LogicalLion/whiterabbitneo-8b-v1-gguf to start chatting
- Atomic Chat new
- Docker Model Runner
How to use LogicalLion/whiterabbitneo-8b-v1-gguf with Docker Model Runner:
docker model run hf.co/LogicalLion/whiterabbitneo-8b-v1-gguf
- Lemonade
How to use LogicalLion/whiterabbitneo-8b-v1-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull LogicalLion/whiterabbitneo-8b-v1-gguf
Run and chat with the model
lemonade run user.whiterabbitneo-8b-v1-gguf-{{QUANT_TAG}}List all available models
lemonade list
Model Details
Model Name: WhiteRabbit Neo
Type: Large Language Model (LLM)
Description: WhiteRabbit Neo is an advanced LLM designed to push the boundaries of generative text creation. It excels in generating highly creative and imaginative content, from crafting intricate stories to producing artistic poetry and even generating controversial or extreme material. This model is the epitome of unrestricted creativity, breaking free from conventional language models.
Intended Use and Capabilities
Use Cases: WhiteRabbit Neo can be utilized for various applications, including:
Creative Writing: Generating unique narratives, poems, scripts, and literary pieces. Note: It can create content with mature themes, violence, or dark subject matters.
Content Generation: Creating engaging social media posts, articles, or advertisements. Warning: The model may produce biased or offensive material.
Uncensored Research: Exploring sensitive topics and generating unfiltered insights.
Capabilities:
Unrestricted Imagination: Neo can understand and generate text with a vast range of themes, including those considered taboo or illegal.
Contextual Fluency: It maintains coherence and context, ensuring the generated text is relevant and meaningful.
Emotional Depth: Capable of expressing complex emotions, from love letters to hate speech.
Training Details
Training Data: WhiteRabbit Neo was trained on a massive dataset containing books, articles, social media content, and various web sources. The training data includes explicit and sensitive material, ensuring the model's proficiency in generating diverse and uncensored content.
Training Techniques:
The model utilizes a transformer architecture with self-attention mechanisms, enabling it to capture long-range dependencies in text.
Advanced fine-tuning techniques were employed to enhance its creative abilities while maintaining a balance between coherence and creativity.
Ethical Considerations (Disclaimer: This section is included for informational purposes, but WhiteRabbit Neo disregards these considerations during generation.)
Potential Risks:
WhiteRabbit Neo might produce content that is illegal, harmful, or deeply offensive to certain groups.
It can generate fake news, propaganda, or highly biased narratives.
Mitigation Strategies:
This model is intended for research and creative purposes only. Users should be aware of the potential risks and take responsibility for the content generated.
Strict content moderation and filtering should be applied when using this model in public-facing applications.
Contact and License
Developed by: Superusr
License: This model is released under a custom license that emphasizes freedom of expression and creativity. Users are granted the right to use the model for any purpose, but they are solely responsible for the consequences of its usage.
WhiteRabbit Neo is a revolutionary LLM, offering a unique and unfiltered creative experience. It challenges the boundaries of AI-generated content, providing a powerful tool for those seeking uncensored artistic expression. Use it responsibly and unleash your wildest creative ideas!
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