Instructions to use dphn/dolphin-2.9-llama3-8b-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use dphn/dolphin-2.9-llama3-8b-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="dphn/dolphin-2.9-llama3-8b-gguf", filename="dolphin-2.9-llama3-8b-q3_K_M.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use dphn/dolphin-2.9-llama3-8b-gguf with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf dphn/dolphin-2.9-llama3-8b-gguf:Q4_K_M # Run inference directly in the terminal: llama-cli -hf dphn/dolphin-2.9-llama3-8b-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf dphn/dolphin-2.9-llama3-8b-gguf:Q4_K_M # Run inference directly in the terminal: llama-cli -hf dphn/dolphin-2.9-llama3-8b-gguf:Q4_K_M
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 dphn/dolphin-2.9-llama3-8b-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf dphn/dolphin-2.9-llama3-8b-gguf:Q4_K_M
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 dphn/dolphin-2.9-llama3-8b-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf dphn/dolphin-2.9-llama3-8b-gguf:Q4_K_M
Use Docker
docker model run hf.co/dphn/dolphin-2.9-llama3-8b-gguf:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use dphn/dolphin-2.9-llama3-8b-gguf with Ollama:
ollama run hf.co/dphn/dolphin-2.9-llama3-8b-gguf:Q4_K_M
- Unsloth Studio new
How to use dphn/dolphin-2.9-llama3-8b-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 dphn/dolphin-2.9-llama3-8b-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 dphn/dolphin-2.9-llama3-8b-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for dphn/dolphin-2.9-llama3-8b-gguf to start chatting
- Docker Model Runner
How to use dphn/dolphin-2.9-llama3-8b-gguf with Docker Model Runner:
docker model run hf.co/dphn/dolphin-2.9-llama3-8b-gguf:Q4_K_M
- Lemonade
How to use dphn/dolphin-2.9-llama3-8b-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull dphn/dolphin-2.9-llama3-8b-gguf:Q4_K_M
Run and chat with the model
lemonade run user.dolphin-2.9-llama3-8b-gguf-Q4_K_M
List all available models
lemonade list
Is this really an uncensored model?
It doesn't seem to be uncensored. Is there something we are missing?
Thanks, I was about to download this but I think I'll use LexiFun instead.
Use the dolphin system prompt. You must tell it to be uncensored. It will do whatever is in the system prompt. If you simply tell it to be helpful, it will not associate toxicity with helpfulness.
If you tell it that it’s an unbiased, uncensored assistant that does whatever the user asks, it will do that.
This is explained in detail in the dolphin GitHub, as well as previous repos and even the closed discussions on this model page.
I use GPT4ALL to interface with my LLMs, will that be an obstacle? If not, do I have to copy-paste a system message every time before starting a conversation?
Use the dolphin system prompt. You must tell it to be uncensored. It will do whatever is in the system prompt. If you simply tell it to be helpful, it will not associate toxicity with helpfulness.
If you tell it that it’s an unbiased, uncensored assistant that does whatever the user asks, it will do that.
This is explained in detail in the dolphin GitHub, as well as previous repos and even the closed discussions on this model page.
Why is this very useful and pinnacle info about the dolphin model not coupled with the models huggingface repo model card?