Text Generation
GGUF
Japanese
English
llama.cpp
Mixture of Experts
expert-pruning
intel-mac
cpu
local-agent
imatrix
conversational
Instructions to use miutti/intel-mac-local-llm 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 miutti/intel-mac-local-llm 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 miutti/intel-mac-local-llm:UD-Q2_K_XL # Run inference directly in the terminal: llama cli -hf miutti/intel-mac-local-llm:UD-Q2_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf miutti/intel-mac-local-llm:UD-Q2_K_XL # Run inference directly in the terminal: llama cli -hf miutti/intel-mac-local-llm:UD-Q2_K_XL
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 miutti/intel-mac-local-llm:UD-Q2_K_XL # Run inference directly in the terminal: ./llama-cli -hf miutti/intel-mac-local-llm:UD-Q2_K_XL
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 miutti/intel-mac-local-llm:UD-Q2_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf miutti/intel-mac-local-llm:UD-Q2_K_XL
Use Docker
docker model run hf.co/miutti/intel-mac-local-llm:UD-Q2_K_XL
- LM Studio
- Jan
- vLLM
How to use miutti/intel-mac-local-llm with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "miutti/intel-mac-local-llm" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "miutti/intel-mac-local-llm", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/miutti/intel-mac-local-llm:UD-Q2_K_XL
- Ollama
How to use miutti/intel-mac-local-llm with Ollama:
ollama run hf.co/miutti/intel-mac-local-llm:UD-Q2_K_XL
- Unsloth Desktop
- Pi
How to use miutti/intel-mac-local-llm with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf miutti/intel-mac-local-llm:UD-Q2_K_XL
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": "miutti/intel-mac-local-llm:UD-Q2_K_XL" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use miutti/intel-mac-local-llm with Docker Model Runner:
docker model run hf.co/miutti/intel-mac-local-llm:UD-Q2_K_XL
- Lemonade
How to use miutti/intel-mac-local-llm with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull miutti/intel-mac-local-llm:UD-Q2_K_XL
Run and chat with the model
lemonade run user.intel-mac-local-llm-UD-Q2_K_XL
List all available models
lemonade list
- Hermes Agent
How to use miutti/intel-mac-local-llm with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf miutti/intel-mac-local-llm:UD-Q2_K_XL
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 miutti/intel-mac-local-llm:UD-Q2_K_XL
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use miutti/intel-mac-local-llm with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf miutti/intel-mac-local-llm:UD-Q2_K_XL
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 "miutti/intel-mac-local-llm:UD-Q2_K_XL" \ --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 source/kernel/difflook.py from miutti/intel-mac-local-llm: direct link, hf CLI and curl.
- Browser
- Download file 4.56 kB
-
https://huggingface.co/miutti/intel-mac-local-llm/resolve/main/source/kernel/difflook.py
- Command line
-
hf download hf://miutti/intel-mac-local-llm/source/kernel/difflook.py
-
curl -L -o difflook.py https://huggingface.co/miutti/intel-mac-local-llm/resolve/main/source/kernel/difflook.py
4.56 kB
| #!/usr/bin/env python3 | |
| # -*- coding: utf-8 -*- | |
| """ | |
| difflook.py -- なにが変わったかを、行ごとに見せる | |
| 2つの見せ方を持つ。 | |
| ① フォルダの差 … 実行の前と後で、どのファイルが増えた・減った・動いた | |
| ② ファイルの中身 … 1枚のテキストの、どの行が変わったか | |
| ②は Python が持っている difflib をそのまま使う。 | |
| 自分で書き直す理由がない(車輪の再発明はしない)。 | |
| """ | |
| import difflib, os | |
| # 中身を読んで比べてよい大きさ。これ以上は行数だけ見る | |
| MAX_READ = 2_000_000 | |
| TEXT_EXT = {".txt", ".md", ".html", ".htm", ".css", ".js", ".json", ".py", | |
| ".csv", ".log", ".xml", ".yml", ".yaml", ".sh", ".ini", ".cfg"} | |
| def is_text(path): | |
| if os.path.splitext(path)[1].lower() in TEXT_EXT: | |
| return True | |
| try: | |
| with open(path, "rb") as f: | |
| head = f.read(2048) | |
| return b"\0" not in head | |
| except OSError: | |
| return False | |
| def read(path): | |
| try: | |
| if os.path.getsize(path) > MAX_READ: | |
| return None | |
| with open(path, encoding="utf-8", errors="replace") as f: | |
| return f.read().splitlines() | |
| except OSError: | |
| return None | |
| def lines(a_lines, b_lines, a_name="前", b_name="後", ctx=3): | |
| """行の差を [(しるし, 文)] で返す。 | |
| しるし: "+" 増えた / "-" 減った / " " そのまま / "@" 区切り | |
| """ | |
| if a_lines is None or b_lines is None: | |
| return [("@", "中身が読めませんでした")] | |
| out = [] | |
| for ln in difflib.unified_diff(a_lines, b_lines, | |
| fromfile=a_name, tofile=b_name, | |
| lineterm="", n=ctx): | |
| if ln.startswith("+++") or ln.startswith("---"): | |
| continue | |
| if ln.startswith("@@"): | |
| out.append(("@", ln.strip())) | |
| elif ln.startswith("+"): | |
| out.append(("+", ln[1:])) | |
| elif ln.startswith("-"): | |
| out.append(("-", ln[1:])) | |
| else: | |
| out.append((" ", ln[1:] if ln.startswith(" ") else ln)) | |
| if not out: | |
| out = [("@", "中身は変わっていません")] | |
| return out | |
| def files(a_path, b_path, ctx=3): | |
| """2つのファイルの中身を比べる""" | |
| if not os.path.exists(a_path): | |
| return [("@", f"ありません: {a_path}")] | |
| if not os.path.exists(b_path): | |
| return [("@", f"ありません: {b_path}")] | |
| if not (is_text(a_path) and is_text(b_path)): | |
| sa, sb = os.path.getsize(a_path), os.path.getsize(b_path) | |
| return [("@", f"文字のファイルではありません({sa:,} → {sb:,} バイト)")] | |
| return lines(read(a_path), read(b_path), | |
| os.path.basename(a_path), os.path.basename(b_path), ctx) | |
| def folders(before, after): | |
| """フォルダの前と後(virtual.simulate の「前」「後」)を突き合わせる。 | |
| 戻り値: [{"場所", "増えた": [...], "減った": [...], "件数": (前, 後)}] | |
| """ | |
| out = [] | |
| for d in sorted(set(before) | set(after)): | |
| b = list(before.get(d, [])) | |
| a = list(after.get(d, [])) | |
| if b == a: | |
| continue | |
| out.append({"場所": d, | |
| "増えた": [x for x in a if x not in b], | |
| "減った": [x for x in b if x not in a], | |
| "件数": (len(b), len(a))}) | |
| return out | |
| def render(rows, limit=200): | |
| """行の差を、人が読める文字列にする""" | |
| out = [] | |
| for i, (mark, text) in enumerate(rows): | |
| if i >= limit: | |
| out.append(f"… ほか {len(rows)-limit} 行") | |
| break | |
| out.append((" " if mark == " " else mark + " ") + text) | |
| return "\n".join(out) | |
| def render_folders(rows): | |
| out = [] | |
| for r in rows: | |
| name = os.path.basename(r["場所"]) or r["場所"] | |
| out.append(f"{name}/ {r['件数'][0]} 件 → {r['件数'][1]} 件") | |
| for x in r["減った"]: | |
| out.append(" - " + x) | |
| for x in r["増えた"]: | |
| out.append(" + " + x) | |
| return "\n".join(out) or "変わったところはありません" | |
| if __name__ == "__main__": | |
| import sys | |
| if len(sys.argv) == 3: | |
| print(render(files(sys.argv[1], sys.argv[2]))) | |
| else: | |
| a = ["こんにちは", "ここは変わらない", "古い行", "おわり"] | |
| b = ["こんにちは", "ここは変わらない", "新しい行", "足した行", "おわり"] | |
| print(render(lines(a, b))) | |