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 (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -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 serve -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 serve -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 serve -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
- Atomic Chat new
- 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: 1,962 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 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | {
"binary_compatibility": {
"base_container": "GGUF",
"base_container_version": 3,
"runtime_target": "Ollama / llama.cpp compatible GGUF loader",
"sidecar_required_for_tinymind_features": true
},
"claim_rules": {
"may_claim_better_than_gguf_v3": false,
"may_claim_binary_gguf_v3_compatibility": true,
"may_claim_custom_tinymind_format_pack": true,
"may_claim_weights_retrained_inside_gguf": false,
"required_to_unlock_better_than_v3_claim": [
"real adapter-to-GGUF merge/export log",
"baseline GGUF v3 eval",
"GGUF-X eval on same prompts",
"latency/memory report",
"hashes for every artifact"
]
},
"format_kind": "GGUF-v3-compatible-binary-plus-TinyMind-sidecar",
"schema_version": "tinymind-gguf-x-v1",
"tinymind_extensions": {
"adapter_lineage_gate": {
"adapter_manifest": "model\\tinymind-12b\\adapters\\tinymind-12b-ggufx-purecode-lr3e7-s4-25690527_232007\\tinymind_12b_manifest.json",
"enabled": true,
"purpose": "separate trained LoRA evidence from GGUF packaging evidence",
"training_manifest": "model\\tinymind-12b\\adapters\\tinymind-12b-ggufx-purecode-lr3e7-s4-25690527_232007\\tinymind_12b_manifest.json"
},
"evidence_first_decode_law": {
"enabled": true,
"purpose": "reduce hallucination/repetition without pretending the GGUF weights changed",
"repeat_penalty": 1.19,
"temperature": 0.14,
"top_p": 0.78
},
"purity_lineage_gate": {
"enabled": true,
"manifest": "reports\\purity_concentrator_code_puremax_latest\\purity_concentrator_manifest.json",
"purpose": "tie runtime claims to the exact purity-concentrated dataset used for adapter training"
},
"regen_ledger_ready_metadata": {
"enabled": true,
"kv_growth_claim": "bounded only when paired with Evidence Ledger/ReGenesis retrieval runtime"
}
}
}
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