Instructions to use Lewdiculous/Datura_7B-GGUF-Imatrix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Lewdiculous/Datura_7B-GGUF-Imatrix 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 Lewdiculous/Datura_7B-GGUF-Imatrix:Q4_K_M # Run inference directly in the terminal: llama cli -hf Lewdiculous/Datura_7B-GGUF-Imatrix:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Lewdiculous/Datura_7B-GGUF-Imatrix:Q4_K_M # Run inference directly in the terminal: llama cli -hf Lewdiculous/Datura_7B-GGUF-Imatrix:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf Lewdiculous/Datura_7B-GGUF-Imatrix:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf Lewdiculous/Datura_7B-GGUF-Imatrix:Q4_K_M
Use Docker
docker model run hf.co/Lewdiculous/Datura_7B-GGUF-Imatrix:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use Lewdiculous/Datura_7B-GGUF-Imatrix with Ollama:
ollama run hf.co/Lewdiculous/Datura_7B-GGUF-Imatrix:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Lewdiculous/Datura_7B-GGUF-Imatrix with Docker Model Runner:
docker model run hf.co/Lewdiculous/Datura_7B-GGUF-Imatrix:Q4_K_M
- Lemonade
How to use Lewdiculous/Datura_7B-GGUF-Imatrix with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Lewdiculous/Datura_7B-GGUF-Imatrix:Q4_K_M
Run and chat with the model
lemonade run user.Datura_7B-GGUF-Imatrix-Q4_K_M
List all available models
lemonade list
- Atomic Chat
This repository hosts GGUF-Imatrix quantizations for ResplendentAI/Datura_7B.
Base⇢ GGUF(F16)⇢ Imatrix-Data(F16)⇢ GGUF(Imatrix-Quants)
quantization_options = [
"Q4_K_M", "Q5_K_M", "Q6_K", "Q8_0"
]
This is experimental.
For imatrix data generation, kalomaze's groups_merged.txt with added roleplay chats was used, you can find it here.
The goal is to measure the (hopefully positive) impact of this data for consistent formatting in roleplay chatting scenarios.
Original model information:
Datura 7B
Flora with a bit of toxicity.
I've been making progress with my collection of tools, so I thought maybe I'd try something a little more toxic for this space. This should make for a more receptive model with fewer refusals.
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