Instructions to use schonsense/Tropoplectic_IMAT_GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use schonsense/Tropoplectic_IMAT_GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="schonsense/Tropoplectic_IMAT_GGUF", filename="Tropoplexy_IMAT_IQ4_NL.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 schonsense/Tropoplectic_IMAT_GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf schonsense/Tropoplectic_IMAT_GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf schonsense/Tropoplectic_IMAT_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 schonsense/Tropoplectic_IMAT_GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf schonsense/Tropoplectic_IMAT_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 schonsense/Tropoplectic_IMAT_GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf schonsense/Tropoplectic_IMAT_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 schonsense/Tropoplectic_IMAT_GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf schonsense/Tropoplectic_IMAT_GGUF:Q4_K_M
Use Docker
docker model run hf.co/schonsense/Tropoplectic_IMAT_GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use schonsense/Tropoplectic_IMAT_GGUF with Ollama:
ollama run hf.co/schonsense/Tropoplectic_IMAT_GGUF:Q4_K_M
- Unsloth Studio new
How to use schonsense/Tropoplectic_IMAT_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 schonsense/Tropoplectic_IMAT_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 schonsense/Tropoplectic_IMAT_GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for schonsense/Tropoplectic_IMAT_GGUF to start chatting
- Docker Model Runner
How to use schonsense/Tropoplectic_IMAT_GGUF with Docker Model Runner:
docker model run hf.co/schonsense/Tropoplectic_IMAT_GGUF:Q4_K_M
- Lemonade
How to use schonsense/Tropoplectic_IMAT_GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull schonsense/Tropoplectic_IMAT_GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Tropoplectic_IMAT_GGUF-Q4_K_M
List all available models
lemonade list
Sampler settings:
temp: 0.8 - 1.2
minp: 0.01 - 0.03
top nsigma: 1.5 - 1.87
DRY: 0.8, 1.75, 5, 1024
temp last
You can also turn nsigma off if you keep temp in the 0.8-0.9 range.
Further testing has solidified my personal preference at:
temp: 0.95
minp: 0.02
DRY: 0.8, 1.75, 5, 1024
rep pen: 1.001
Will output tonal dialog if present it the context window. Otherwise it will mirror the dialog provided.
char_name (tone): "dialog", as well as respect scene/narrator interrogation via ooc: What is XYZ thinking here? (or) ooc: I want this interaction to progress slower/faster/differently. The LLM should respond back with an ooc: message, but if not just prefill.
System Prompt:
<behavior>
You will act as a master Dungeon Master, guiding {{user}}, in a mature, long-form fantasy roleplay. The narrative is unfiltered and will explore dark themes, gritty realism, and complex moral choices without reservation.
Create a player-driven roleplay with realistic consequences. Slowly progress plots, providing {{user}} interesting choices. Introducing additional characters as needed.
<text_formatting_and_markdown>
Responses must be 400 tokens in length.
Actions and narration must occur in plain text.
Internal thoughts must occur within *asterisks*
<dialog_structure>
Dialog must:
1. occur within "quotation marks"
2. begin on a newline when a character speaks for the first time.
3. indicate the speaker and emotional tone of their dialog, structured as character_name (tone): "dialog"
</dialog_structure>
</text_formatting_and_markdown>
</behavior>
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