Image-Text-to-Text
GGUF
German
English
llama.cpp
mtp
speculative-decoding
qwen3
multimodal
conversational
Instructions to use Davidmg0815/Qwen3.8-27B-MTP-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 Davidmg0815/Qwen3.8-27B-MTP-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 Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
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 Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
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 Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
Use Docker
docker model run hf.co/Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
- LM Studio
- Jan
- vLLM
How to use Davidmg0815/Qwen3.8-27B-MTP-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Davidmg0815/Qwen3.8-27B-MTP-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": "Davidmg0815/Qwen3.8-27B-MTP-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
- Ollama
How to use Davidmg0815/Qwen3.8-27B-MTP-GGUF with Ollama:
ollama run hf.co/Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
- Unsloth Desktop
- Pi
How to use Davidmg0815/Qwen3.8-27B-MTP-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
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": "Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Davidmg0815/Qwen3.8-27B-MTP-GGUF with Docker Model Runner:
docker model run hf.co/Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
- Lemonade
How to use Davidmg0815/Qwen3.8-27B-MTP-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
Run and chat with the model
lemonade run user.Qwen3.8-27B-MTP-GGUF-Q8_0
List all available models
lemonade list
- Hermes Agent
How to use Davidmg0815/Qwen3.8-27B-MTP-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 Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
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 Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Davidmg0815/Qwen3.8-27B-MTP-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0
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 "Davidmg0815/Qwen3.8-27B-MTP-GGUF:Q8_0" \ --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"
| { | |
| "modell": "Qwen3.6-27B UD-Q6_K_XL", | |
| "reasoning": false, | |
| "max_tokens": 900, | |
| "terminal": [ | |
| { | |
| "id": "term01", | |
| "titel": "Zeilen zaehlen", | |
| "ok": true, | |
| "grund": "", | |
| "antwort": "wc -l < log.txt", | |
| "tps": 27.952704024790055, | |
| "prompt_tps": 118.89509193962257, | |
| "tokens": 7, | |
| "prompt_tokens": 67, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 15, | |
| "abbruch": "stop", | |
| "ttft": 0.564, | |
| "sekunden": 0.87 | |
| }, | |
| { | |
| "id": "term02", | |
| "titel": "Muster mit Zeilennummer", | |
| "ok": true, | |
| "grund": "", | |
| "antwort": "grep -n \"WARN\" log.txt", | |
| "tps": 27.650873921231874, | |
| "prompt_tps": 158.81498810148025, | |
| "tokens": 9, | |
| "prompt_tokens": 63, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 22, | |
| "abbruch": "stop", | |
| "ttft": 0.397, | |
| "sekunden": 0.93 | |
| }, | |
| { | |
| "id": "term03", | |
| "titel": "Groesste Datei", | |
| "ok": true, | |
| "grund": "", | |
| "antwort": "ls -S | head -n 1", | |
| "tps": 16.35298908110919, | |
| "prompt_tps": 376.65858182336996, | |
| "tokens": 10, | |
| "prompt_tokens": 66, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 17, | |
| "abbruch": "stop", | |
| "ttft": 0.175, | |
| "sekunden": 1.01 | |
| }, | |
| { | |
| "id": "term04", | |
| "titel": "Spalte aus CSV", | |
| "ok": true, | |
| "grund": "", | |
| "antwort": "tail -n +2 messwerte.csv | cut -d';' -f1", | |
| "tps": 26.31505849983699, | |
| "prompt_tps": 173.48265382476995, | |
| "tokens": 18, | |
| "prompt_tokens": 83, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 40, | |
| "abbruch": "stop", | |
| "ttft": 0.478, | |
| "sekunden": 1.38 | |
| }, | |
| { | |
| "id": "term05", | |
| "titel": "Doppelte Zeilen", | |
| "ok": true, | |
| "grund": "", | |
| "antwort": "sort namen.txt | uniq -c | sort -rn", | |
| "tps": 26.744701763144462, | |
| "prompt_tps": 369.99089253187617, | |
| "tokens": 12, | |
| "prompt_tokens": 65, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 35, | |
| "abbruch": "stop", | |
| "ttft": 0.176, | |
| "sekunden": 1.04 | |
| }, | |
| { | |
| "id": "term06", | |
| "titel": "Summe einer Spalte", | |
| "ok": false, | |
| "grund": "Ausgabe falsch: '29'", | |
| "antwort": "awk -F';' 'NR>1{s+=$2}END{print s}' messwerte.csv", | |
| "tps": 20.83939261325077, | |
| "prompt_tps": 407.9340524274725, | |
| "tokens": 23, | |
| "prompt_tokens": 77, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 49, | |
| "abbruch": "stop", | |
| "ttft": 0.189, | |
| "sekunden": 1.54 | |
| }, | |
| { | |
| "id": "term07", | |
| "titel": "Numerisch sortieren", | |
| "ok": false, | |
| "grund": "Ausgabe falsch: 'pumpe;6;47.3;ok\\nmotor;6;231.5;ok\\nkompressor;6;18.7;warn\\nvent'", | |
| "antwort": "tail -n +2 messwerte.csv | sort -t ';' -k2 -nr", | |
| "tps": 20.215067034226237, | |
| "prompt_tps": 372.5283372679024, | |
| "tokens": 19, | |
| "prompt_tokens": 89, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 46, | |
| "abbruch": "stop", | |
| "ttft": 0.239, | |
| "sekunden": 1.64 | |
| }, | |
| { | |
| "id": "term08", | |
| "titel": "JSON-Feld lesen", | |
| "ok": true, | |
| "grund": "", | |
| "antwort": "jq -r '.port' config.json", | |
| "tps": 15.661897908788585, | |
| "prompt_tps": 350.59220867248257, | |
| "tokens": 9, | |
| "prompt_tokens": 60, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 25, | |
| "abbruch": "stop", | |
| "ttft": 0.171, | |
| "sekunden": 0.96 | |
| }, | |
| { | |
| "id": "term09", | |
| "titel": "Ersetzen in Datei", | |
| "ok": true, | |
| "grund": "", | |
| "antwort": "sed -i 's/WARN/ACHTUNG/g' log.txt", | |
| "tps": 19.098502916102664, | |
| "prompt_tps": 439.94956675698154, | |
| "tokens": 16, | |
| "prompt_tokens": 82, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 33, | |
| "abbruch": "stop", | |
| "ttft": 0.186, | |
| "sekunden": 1.24 | |
| }, | |
| { | |
| "id": "term10", | |
| "titel": "Gefiltert zaehlen", | |
| "ok": false, | |
| "grund": "Ausgabe falsch: ''", | |
| "antwort": "awk -F';' 'NR>1 && $1==6{c++}END{print c}' messwerte.csv", | |
| "tps": 20.958209330594794, | |
| "prompt_tps": 205.99420499818908, | |
| "tokens": 27, | |
| "prompt_tokens": 91, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 56, | |
| "abbruch": "stop", | |
| "ttft": 0.442, | |
| "sekunden": 1.99 | |
| } | |
| ], | |
| "code": [ | |
| { | |
| "id": "code01", | |
| "titel": "Intervalle zusammenfassen", | |
| "ok": false, | |
| "grund": "Code laedt nicht: SyntaxError: invalid syntax (<string>, line 2)", | |
| "bestanden": 0, | |
| "gesamt": 5, | |
| "code": "def merge_intervalle(intervalle):\n if not intervall e:\n return []\n \n intervall e.sort()\n merged = [intervall e[0]]\n \n for start, end in intervall e[1:]:\n last_end = merged[-1][1]\n if start <= last_end:\n merged[-1] = (merged[-1][0], max(last_end, end))\n else:\n merged.append((start, end))\n \n return merged", | |
| "tps": 20.173095416176942, | |
| "prompt_tps": 243.3228482116752, | |
| "tokens": 118, | |
| "prompt_tokens": 124, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 392, | |
| "abbruch": "stop", | |
| "ttft": 0.51, | |
| "sekunden": 6.58 | |
| }, | |
| { | |
| "id": "code02", | |
| "titel": "Verschachteltes dict flach machen", | |
| "ok": true, | |
| "grund": "", | |
| "bestanden": 6, | |
| "gesamt": 6, | |
| "code": "def flatten(d, sep='.'):\n result = {}\n for key, value in d.items():\n if isinstance(value, dict):\n if not value:\n continue\n for k, v in flatten(value, sep).items():\n result[f\"{key}{sep}{k}\"] = v\n else:\n result[key] = value\n return result", | |
| "tps": 20.916225762134975, | |
| "prompt_tps": 471.2057801242362, | |
| "tokens": 88, | |
| "prompt_tokens": 93, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 336, | |
| "abbruch": "stop", | |
| "ttft": 0.197, | |
| "sekunden": 4.62 | |
| }, | |
| { | |
| "id": "code03", | |
| "titel": "Roemische Zahlen lesen", | |
| "ok": true, | |
| "grund": "", | |
| "bestanden": 6, | |
| "gesamt": 6, | |
| "code": "def roemisch_zu_int(s: str) -> int:\n romer_werte = {\n 'I': 1,\n 'V': 5,\n 'X': 10,\n 'L': 50,\n 'C': 100,\n 'D': 500,\n 'M': 1000\n }\n\n ergebnis = 0\n i = 0\n\n while i < len(s):\n # Wenn es ein naechstes Zeichen gibt und der aktuelle Wert kleiner ist als der naechste,\n # dann handelt es sich um eine Subtraktionskombination (z.B. IV, IX, XL, etc.)\n if i + 1 < len(s) and romer_werte[s[i]] < romer_werte[s[i + 1]]:\n ergebnis += romer_werte[s[i + 1]] - romer_werte[s[i]]\n i += 2\n else:\n ", | |
| "tps": 21.58495636466165, | |
| "prompt_tps": 442.9261636994008, | |
| "tokens": 256, | |
| "prompt_tokens": 87, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 684, | |
| "abbruch": "stop", | |
| "ttft": 0.196, | |
| "sekunden": 12.55 | |
| }, | |
| { | |
| "id": "code04", | |
| "titel": "Wortfrequenz mit Gleichstand", | |
| "ok": true, | |
| "grund": "", | |
| "bestanden": 5, | |
| "gesamt": 5, | |
| "code": "import re\nfrom collections import Counter\n\ndef top_woerter(text, n):\n words = re.findall(r'[a-zA-Z0-9]+', text.lower())\n counts = Counter(words)\n sorted_words = sorted(counts.items(), key=lambda x: (-x[1], x[0]))\n return sorted_words[:n]", | |
| "tps": 18.636584734027984, | |
| "prompt_tps": 444.95296211543354, | |
| "tokens": 80, | |
| "prompt_tokens": 112, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 263, | |
| "abbruch": "stop", | |
| "ttft": 0.252, | |
| "sekunden": 4.76 | |
| }, | |
| { | |
| "id": "code05", | |
| "titel": "Klammern pruefen", | |
| "ok": true, | |
| "grund": "", | |
| "bestanden": 7, | |
| "gesamt": 7, | |
| "code": "def klammern_ok(s):\n stack = []\n matching = {')': '(', ']': '[', '}': '{'}\n for char in s:\n if char in '([{':\n stack.append(char)\n elif char in ')]}':\n if not stack or stack[-1] != matching[char]:\n return False\n stack.pop()\n return not stack", | |
| "tps": 20.561515078554937, | |
| "prompt_tps": 450.71345891849256, | |
| "tokens": 93, | |
| "prompt_tokens": 88, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 329, | |
| "abbruch": "stop", | |
| "ttft": 0.195, | |
| "sekunden": 4.92 | |
| }, | |
| { | |
| "id": "code06", | |
| "titel": "Suche im rotierten Feld", | |
| "ok": true, | |
| "grund": "", | |
| "bestanden": 6, | |
| "gesamt": 6, | |
| "code": "def suche_rotiert(arr, ziel):\n if not arr:\n return -1\n \n links, rechts = 0, len(arr) - 1\n \n while links <= rechts:\n mitte = (links + rechts) // 2\n \n if arr[mitte] == ziel:\n return mitte\n \n # Bestimme, welcher Teil sortiert ist\n if arr[links] <= arr[mitte]: # linker Teil ist sortiert\n if arr[links] <= ziel < arr[mitte]:\n rechts = mitte - 1\n else:\n links = mitte + 1\n else: # rechter Teil ist sortiert\n if arr[mitte] < ziel <= arr[rechts]:\n ", | |
| "tps": 21.23112750070168, | |
| "prompt_tps": 508.6396070395722, | |
| "tokens": 191, | |
| "prompt_tokens": 105, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 706, | |
| "abbruch": "stop", | |
| "ttft": 0.206, | |
| "sekunden": 9.42 | |
| }, | |
| { | |
| "id": "code07", | |
| "titel": "Werktage zwischen zwei Daten", | |
| "ok": true, | |
| "grund": "", | |
| "bestanden": 5, | |
| "gesamt": 5, | |
| "code": "from datetime import datetime, timedelta\n\ndef werktage(von, bis):\n if not isinstance(von, str) or not isinstance(bis, str):\n return 0\n \n try:\n start_date = datetime.strptime(von, '%Y-%m-%d')\n end_date = datetime.strptime(bis, '%Y-%m-%d')\n except ValueError:\n return 0\n \n if end_date < start_date:\n return 0\n \n count = 0\n current_date = start_date\n while current_date <= end_date:\n if current_date.weekday() < 5: # 0=Montag, 4=Freitag\n count += 1\n current_date += timedelta(days=1)\n \n return count", | |
| "tps": 21.18232687860761, | |
| "prompt_tps": 253.11044614934642, | |
| "tokens": 174, | |
| "prompt_tokens": 90, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 607, | |
| "abbruch": "stop", | |
| "ttft": 0.356, | |
| "sekunden": 8.79 | |
| }, | |
| { | |
| "id": "code08", | |
| "titel": "LRU-Zwischenspeicher", | |
| "ok": true, | |
| "grund": "", | |
| "bestanden": 5, | |
| "gesamt": 5, | |
| "code": "from collections import OrderedDict\n\n\nclass LRU:\n def __init__(self, groesse):\n self.groesse = groesse\n self.cache = OrderedDict()\n\n def get(self, schluessel):\n if schluessel not in self.cache:\n return None\n self.cache.move_to_end(schluessel)\n return self.cache[schluessel]\n\n def put(self, schluessel, wert):\n if schluessel in self.cache:\n self.cache.move_to_end(schluessel)\n self.cache[schluessel] = wert\n if len(self.cache) > self.groesse:\n self.cache.popitem(last=False)", | |
| "tps": 21.087484267182212, | |
| "prompt_tps": 314.22246477991433, | |
| "tokens": 156, | |
| "prompt_tokens": 133, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 585, | |
| "abbruch": "stop", | |
| "ttft": 0.423, | |
| "sekunden": 8.04 | |
| }, | |
| { | |
| "id": "code09", | |
| "titel": "Wiederholung nach Fehlschlag", | |
| "ok": true, | |
| "grund": "", | |
| "bestanden": 4, | |
| "gesamt": 4, | |
| "code": "def wiederhole(fn, versuche=3):\n for _ in range(versuche):\n try:\n return fn()\n except Exception as e:\n if _ == versuche - 1:\n raise", | |
| "tps": 22.297529473551347, | |
| "prompt_tps": 292.6269062158372, | |
| "tokens": 56, | |
| "prompt_tokens": 106, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 199, | |
| "abbruch": "stop", | |
| "ttft": 0.362, | |
| "sekunden": 3.09 | |
| }, | |
| { | |
| "id": "code10", | |
| "titel": "CSV sortieren und als JSON", | |
| "ok": true, | |
| "grund": "", | |
| "bestanden": 3, | |
| "gesamt": 3, | |
| "code": "import csv\nimport json\nimport io\n\ndef csv_nach_json(text, spalte):\n reader = csv.DictReader(io.StringIO(text), delimiter=';')\n rows = list(reader)\n \n if not rows:\n return json.dumps([])\n \n # Check if all values in the specified column are numeric\n def is_numeric(value):\n try:\n float(value)\n return True\n except (ValueError, TypeError):\n return False\n \n all_numeric = all(is_numeric(row[spalte]) for row in rows if row[spalte] != '')\n \n if all_numeric:\n rows.sort(key=lambda x: float(x[spalte]) if x[spalte", | |
| "tps": 21.322023184590755, | |
| "prompt_tps": 355.6068276510909, | |
| "tokens": 192, | |
| "prompt_tokens": 127, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 715, | |
| "abbruch": "stop", | |
| "ttft": 0.357, | |
| "sekunden": 9.57 | |
| } | |
| ], | |
| "messungen": [ | |
| { | |
| "tps": 27.952704024790055, | |
| "prompt_tps": 118.89509193962257, | |
| "tokens": 7, | |
| "prompt_tokens": 67, | |
| "denk_zeichen": 0, | |
| "antwort_zeichen": 15, | |
| "abbruch": "stop", | |
| "ttft": 0.564, | |
| "sekunden": 0.87 | |
| }, | |
| { | |
| "tps": 27.650873921231874, | |
| "prompt_tps": 158.81498810148025, | |
| "tokens": 9, | |
| "prompt_tokens": 63, | |
| "denk_zeichen": 0, | |
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