Instructions to use liminerity/M7-7b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use liminerity/M7-7b-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="liminerity/M7-7b-GGUF", filename="multiverse-experiment-slerp-7b.Q5_K_M.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use liminerity/M7-7b-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 liminerity/M7-7b-GGUF:Q5_K_M # Run inference directly in the terminal: llama cli -hf liminerity/M7-7b-GGUF:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf liminerity/M7-7b-GGUF:Q5_K_M # Run inference directly in the terminal: llama cli -hf liminerity/M7-7b-GGUF:Q5_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 liminerity/M7-7b-GGUF:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf liminerity/M7-7b-GGUF:Q5_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 liminerity/M7-7b-GGUF:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf liminerity/M7-7b-GGUF:Q5_K_M
Use Docker
docker model run hf.co/liminerity/M7-7b-GGUF:Q5_K_M
- LM Studio
- Jan
- Ollama
How to use liminerity/M7-7b-GGUF with Ollama:
ollama run hf.co/liminerity/M7-7b-GGUF:Q5_K_M
- Unsloth Studio
How to use liminerity/M7-7b-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 liminerity/M7-7b-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 liminerity/M7-7b-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for liminerity/M7-7b-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use liminerity/M7-7b-GGUF with Docker Model Runner:
docker model run hf.co/liminerity/M7-7b-GGUF:Q5_K_M
- Lemonade
How to use liminerity/M7-7b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull liminerity/M7-7b-GGUF:Q5_K_M
Run and chat with the model
lemonade run user.M7-7b-GGUF-Q5_K_M
List all available models
lemonade list
Is it censored?
Is the model helpful or censored?
Quantized is alright it’s got a bug where it’ll say “instinstinst” but it seems alright for the most part. More than likely needs to be fine tuned but I’m extremely limited with what I can do atm
Bug in the model itself or in quantized verion (how can bug creep into quantization if not present in original?)?
It is no fun, you can't even make a plan to rob a bank :( or legalize bank robbing. :P
@supercharge19 i have only tryed q5_k quantized. i dont have the computing power to run models like that. the bug came from merging 2 different models together. It has to be finetuned to Iron this out
what suitable (smallest) opensource dataset to use to "iron this out"?
@supercharge19 to be honest man idk im self taught and trying to learn still. Im really just a autistic dude