Text Generation
GGUF
English
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multilingual
darwin
darwin-rsi
recursive-self-improvement
rsi
self-improvement
self-improving-ai
self-evolving
no-human-labels
label-free
reasoning
thinking
chain-of-thought
gpqa
supergpqa
decision-index
typed-decisions
jev
system-2
qwen3.5
27b
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Instructions to use bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use bartowski/FINAL-Bench_Darwin-27B-RSI-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 bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf bartowski/FINAL-Bench_Darwin-27B-RSI-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 bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bartowski/FINAL-Bench_Darwin-27B-RSI-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 bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M
Use Docker
docker model run hf.co/bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M
- Ollama
How to use bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF with Ollama:
ollama run hf.co/bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M
- Lemonade
How to use bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.FINAL-Bench_Darwin-27B-RSI-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M
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 bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Download layouts/FINAL-Bench_Darwin-27B-RSI-IQ2_M.layout.json from bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 13 kB
-
https://huggingface.co/bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF/resolve/main/layouts/FINAL-Bench_Darwin-27B-RSI-IQ2_M.layout.json
- Command line
-
hf download hf://bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF/layouts/FINAL-Bench_Darwin-27B-RSI-IQ2_M.layout.json
-
curl -L -o FINAL-Bench_Darwin-27B-RSI-IQ2_M.layout.json https://huggingface.co/bartowski/FINAL-Bench_Darwin-27B-RSI-GGUF/resolve/main/layouts/FINAL-Bench_Darwin-27B-RSI-IQ2_M.layout.json
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| "token_embd.weight": "q3_k" | |
| }, | |
| "bytes": { | |
| "heuristic_body+embd": 10518425600, | |
| "map_body+embd": 10167316480, | |
| "ratio": 0.9666, | |
| "note": "quantizable, unpinned tensors only; pinned/unquantized tensors are identical in both" | |
| }, | |
| "body_base_share": 0.7, | |
| "body_bpw": 2.876, | |
| "body_bpw_heuristic": 2.992, | |
| "total_params": 26895998464, | |
| "file_bytes_pred": 10272270336, | |
| "file_bpw_pred": 3.055, | |
| "histogram": { | |
| "attn_gate": { | |
| "iq2_s": 36, | |
| "iq4_xs": 11, | |
| "q5_k": 1 | |
| }, | |
| "attn_k": { | |
| "q4_k": 12, | |
| "q5_k": 4 | |
| }, | |
| "attn_output": { | |
| "iq4_xs": 15, | |
| "q5_k": 1 | |
| }, | |
| "attn_q": { | |
| "iq2_s": 15, | |
| "iq3_s": 1 | |
| }, | |
| "attn_qkv": { | |
| "iq2_s": 36, | |
| "iq4_xs": 12 | |
| }, | |
| "attn_v": { | |
| "q5_k": 16 | |
| }, | |
| "ffn_down": { | |
| "iq2_s": 60, | |
| "iq4_xs": 2, | |
| "iq3_xxs": 2 | |
| }, | |
| "ffn_gate": { | |
| "iq2_s": 63, | |
| "iq4_xs": 1 | |
| }, | |
| "ffn_up": { | |
| "iq2_s": 47, | |
| "iq3_s": 16, | |
| "iq4_xs": 1 | |
| }, | |
| "ssm_out": { | |
| "iq4_xs": 47, | |
| "q5_k": 1 | |
| } | |
| }, | |
| "prior": "layout/prior.json", | |
| "pin_rule": "floor", | |
| "embd_cap": "heur", | |
| "generator": "auto_quant_v2.layout", | |
| "generator_key": "3bf8b43e20a68f0b", | |
| "quant_type": "IQ2_M", | |
| "quantize_ftype": "IQ2_M", | |
| "llama_cpp_version": "b11259", | |
| "commit": "880615e1e86d7f7f01cc657a975526bc09577cc7" | |
| } | |