Instructions to use Sweaterdog/MindCraft-LLM-tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sweaterdog/MindCraft-LLM-tuning with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Sweaterdog/MindCraft-LLM-tuning", dtype="auto") - llama-cpp-python
How to use Sweaterdog/MindCraft-LLM-tuning with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Sweaterdog/MindCraft-LLM-tuning", filename="Andy-3.5-beta.F16.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 Sweaterdog/MindCraft-LLM-tuning with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Sweaterdog/MindCraft-LLM-tuning:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Sweaterdog/MindCraft-LLM-tuning:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Sweaterdog/MindCraft-LLM-tuning:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Sweaterdog/MindCraft-LLM-tuning: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 Sweaterdog/MindCraft-LLM-tuning:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Sweaterdog/MindCraft-LLM-tuning: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 Sweaterdog/MindCraft-LLM-tuning:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Sweaterdog/MindCraft-LLM-tuning:Q4_K_M
Use Docker
docker model run hf.co/Sweaterdog/MindCraft-LLM-tuning:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Sweaterdog/MindCraft-LLM-tuning with Ollama:
ollama run hf.co/Sweaterdog/MindCraft-LLM-tuning:Q4_K_M
- Unsloth Studio new
How to use Sweaterdog/MindCraft-LLM-tuning 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 Sweaterdog/MindCraft-LLM-tuning 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 Sweaterdog/MindCraft-LLM-tuning to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Sweaterdog/MindCraft-LLM-tuning to start chatting
- Docker Model Runner
How to use Sweaterdog/MindCraft-LLM-tuning with Docker Model Runner:
docker model run hf.co/Sweaterdog/MindCraft-LLM-tuning:Q4_K_M
- Lemonade
How to use Sweaterdog/MindCraft-LLM-tuning with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Sweaterdog/MindCraft-LLM-tuning:Q4_K_M
Run and chat with the model
lemonade run user.MindCraft-LLM-tuning-Q4_K_M
List all available models
lemonade list
Repeating commands
Maybe I have it setup wrong I am new to everything here but using Andy-v2-qwen.Q5_K_M my model seems to keep repeating !collectBlocks without specifying what block he wants to collect and does this repeatedly.
It can do that sometimes, as of the training dataset, it wasn't very broad in command usage, so often times if the model encounters something new, it doesnt know what to do, and since as of this modelfile templete (which sucks) you can't really change the temperature. Right now, I recommend using other models like Gemini or something on GLHF.chat (which was recently added in the discord server only