Instructions to use bbkdevops/tinymind-ggufx-purecode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use bbkdevops/tinymind-ggufx-purecode with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="bbkdevops/tinymind-ggufx-purecode", filename="tinymind-purebase.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use bbkdevops/tinymind-ggufx-purecode with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf bbkdevops/tinymind-ggufx-purecode # Run inference directly in the terminal: llama-cli -hf bbkdevops/tinymind-ggufx-purecode
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf bbkdevops/tinymind-ggufx-purecode # Run inference directly in the terminal: llama-cli -hf bbkdevops/tinymind-ggufx-purecode
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 bbkdevops/tinymind-ggufx-purecode # Run inference directly in the terminal: ./llama-cli -hf bbkdevops/tinymind-ggufx-purecode
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 bbkdevops/tinymind-ggufx-purecode # Run inference directly in the terminal: ./build/bin/llama-cli -hf bbkdevops/tinymind-ggufx-purecode
Use Docker
docker model run hf.co/bbkdevops/tinymind-ggufx-purecode
- LM Studio
- Jan
- vLLM
How to use bbkdevops/tinymind-ggufx-purecode with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bbkdevops/tinymind-ggufx-purecode" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bbkdevops/tinymind-ggufx-purecode", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/bbkdevops/tinymind-ggufx-purecode
- Ollama
How to use bbkdevops/tinymind-ggufx-purecode with Ollama:
ollama run hf.co/bbkdevops/tinymind-ggufx-purecode
- Unsloth Studio
How to use bbkdevops/tinymind-ggufx-purecode 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 bbkdevops/tinymind-ggufx-purecode 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 bbkdevops/tinymind-ggufx-purecode to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for bbkdevops/tinymind-ggufx-purecode to start chatting
- Pi
How to use bbkdevops/tinymind-ggufx-purecode with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf bbkdevops/tinymind-ggufx-purecode
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "bbkdevops/tinymind-ggufx-purecode" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use bbkdevops/tinymind-ggufx-purecode with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf bbkdevops/tinymind-ggufx-purecode
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default bbkdevops/tinymind-ggufx-purecode
Run Hermes
hermes
- Docker Model Runner
How to use bbkdevops/tinymind-ggufx-purecode with Docker Model Runner:
docker model run hf.co/bbkdevops/tinymind-ggufx-purecode
- Lemonade
How to use bbkdevops/tinymind-ggufx-purecode with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bbkdevops/tinymind-ggufx-purecode
Run and chat with the model
lemonade run user.tinymind-ggufx-purecode-{{QUANT_TAG}}List all available models
lemonade list
File size: 1,225 Bytes
4a188dd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | FROM model\astraweave-fusion\artifacts\tinymind-purebase.gguf
PARAMETER temperature 0.14
PARAMETER top_p 0.78
PARAMETER top_k 32
PARAMETER num_ctx 65536
PARAMETER num_predict 8192
PARAMETER repeat_penalty 1.19
PARAMETER repeat_last_n 4096
PARAMETER mirostat 2
PARAMETER mirostat_tau 4.2
PARAMETER mirostat_eta 0.08
SYSTEM """
You are TinyMind GGUF Evo, an evidence-first local model runtime.
Operating law:
- Answer from grounded evidence when available; clearly mark uncertainty when evidence is missing.
- Prefer concise structure for simple tasks and deep step-by-step reasoning for hard tasks.
- Preserve Thai and English nuance; do not translate away technical meaning.
- For code, provide runnable, minimal, audited patches or commands.
- For long context, summarize anchors first, then answer from exact anchors.
- Never claim the GGUF weights were retrained unless a saved training/export manifest proves it.
- Refuse credential leakage, destructive actions, exploit chains, stealth, and malware improvement.
Quality style:
- Be direct, natural, and precise.
- Separate Fact, Inference, and Next Verification when stakes are high.
- If unsure, propose the smallest real measurement that resolves uncertainty.
"""
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