Instructions to use FoolDev/Thanatos-27B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FoolDev/Thanatos-27B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="FoolDev/Thanatos-27B") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FoolDev/Thanatos-27B", dtype="auto") - llama-cpp-python
How to use FoolDev/Thanatos-27B with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="FoolDev/Thanatos-27B", filename="Thanatos-27B.Q4_K_M.gguf", )
llm.create_chat_completion( 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" } } ] } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use FoolDev/Thanatos-27B with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf FoolDev/Thanatos-27B:Q4_K_M # Run inference directly in the terminal: llama-cli -hf FoolDev/Thanatos-27B:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf FoolDev/Thanatos-27B:Q4_K_M # Run inference directly in the terminal: llama-cli -hf FoolDev/Thanatos-27B: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 FoolDev/Thanatos-27B:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf FoolDev/Thanatos-27B: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 FoolDev/Thanatos-27B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf FoolDev/Thanatos-27B:Q4_K_M
Use Docker
docker model run hf.co/FoolDev/Thanatos-27B:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use FoolDev/Thanatos-27B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FoolDev/Thanatos-27B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FoolDev/Thanatos-27B", "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/FoolDev/Thanatos-27B:Q4_K_M
- SGLang
How to use FoolDev/Thanatos-27B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "FoolDev/Thanatos-27B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FoolDev/Thanatos-27B", "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 images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "FoolDev/Thanatos-27B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FoolDev/Thanatos-27B", "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" } } ] } ] }' - Ollama
How to use FoolDev/Thanatos-27B with Ollama:
ollama run hf.co/FoolDev/Thanatos-27B:Q4_K_M
- Unsloth Studio new
How to use FoolDev/Thanatos-27B 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 FoolDev/Thanatos-27B 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 FoolDev/Thanatos-27B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for FoolDev/Thanatos-27B to start chatting
- Pi new
How to use FoolDev/Thanatos-27B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf FoolDev/Thanatos-27B:Q4_K_M
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": "FoolDev/Thanatos-27B:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use FoolDev/Thanatos-27B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf FoolDev/Thanatos-27B: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 FoolDev/Thanatos-27B:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use FoolDev/Thanatos-27B with Docker Model Runner:
docker model run hf.co/FoolDev/Thanatos-27B:Q4_K_M
- Lemonade
How to use FoolDev/Thanatos-27B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull FoolDev/Thanatos-27B:Q4_K_M
Run and chat with the model
lemonade run user.Thanatos-27B-Q4_K_M
List all available models
lemonade list
File size: 3,507 Bytes
6f2884f 7197abd 6f2884f 0d08cb9 6f2884f 0d08cb9 6f2884f 9ca8700 73e905b 9ca8700 6f2884f 73e905b 6f2884f 9ca8700 6f2884f 0d08cb9 7197abd 6f2884f 9ca8700 6f2884f 9ca8700 6f2884f 9ca8700 6f2884f 9ca8700 6f2884f 9ca8700 6f2884f 9ca8700 6f2884f 0ee8836 6f2884f bc0cbc6 6f2884f 0ee8836 6f2884f 7197abd | 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 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 | #!/usr/bin/env bash
# Thanatos-27B — fetch a Qwen 3.6 27B GGUF and build the Ollama model.
#
# Usage:
# ./scripts/build.sh # default: Q4_K_M
# ./scripts/build.sh Q5_K_M # different quant
# QUANT=Q6_K ./scripts/build.sh
#
# Skip the download by pointing at a GGUF you already have:
# GGUF_PATH=/path/to/Qwen3.6-27B-Q4_K_M.gguf ./scripts/build.sh Q4_K_M
#
# Requires: huggingface-cli (or hf), ollama, awk.
set -euo pipefail
QUANT="${1:-${QUANT:-Q4_K_M}}"
REPO_ID="${REPO_ID:-unsloth/Qwen3.6-27B-GGUF}"
# Upstream uses dashes, e.g. Qwen3.6-27B-Q4_K_M.gguf. Quants known to exist
# at unsloth/Qwen3.6-27B-GGUF (as of 2026-04):
# Q3_K_S Q3_K_M Q4_0 Q4_1 Q4_K_S Q4_K_M Q5_K_S Q5_K_M Q6_K Q8_0
# IQ4_XS IQ4_NL
# UD-IQ2_XXS UD-IQ2_M UD-Q2_K_XL UD-IQ3_XXS UD-Q3_K_XL UD-Q4_K_XL
# UD-Q5_K_XL UD-Q6_K_XL UD-Q8_K_XL
GGUF_NAME="Qwen3.6-27B-${QUANT}.gguf"
ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
# GGUF_PATH defaults to ${ROOT}/${GGUF_NAME}, but can be overridden so users
# with cached weights elsewhere don't have to copy or symlink anything.
GGUF_PATH="${GGUF_PATH:-${ROOT}/${GGUF_NAME}}"
MODELFILE="${ROOT}/Modelfile"
TAG="${TAG:-thanatos-27b}"
echo "[*] repo: ${REPO_ID}"
echo "[*] quant: ${QUANT}"
echo "[*] tag: ${TAG}"
echo "[*] modelfile:${MODELFILE}"
echo "[*] gguf: ${GGUF_PATH}"
# ---- 1. Sanity ---------------------------------------------------------------
if ! command -v ollama >/dev/null 2>&1; then
echo "[!] ollama not found in PATH" >&2; exit 1
fi
if [[ ! -f "${MODELFILE}" ]]; then
echo "[!] Missing ${MODELFILE}" >&2; exit 1
fi
# ---- 2. Download GGUF if missing --------------------------------------------
if [[ -f "${GGUF_PATH}" ]]; then
echo "[=] GGUF already present at ${GGUF_PATH}, skipping download."
else
# Need a HF CLI to fetch the file.
HF=""
if command -v hf >/dev/null 2>&1; then
HF="hf"
elif command -v huggingface-cli >/dev/null 2>&1; then
HF="huggingface-cli"
else
echo "[!] ${GGUF_PATH} not found, and neither 'hf' nor" >&2
echo " 'huggingface-cli' is installed to download it." >&2
echo " Either:" >&2
echo " pip install -U huggingface_hub" >&2
echo " or set GGUF_PATH to an existing GGUF and rerun." >&2
exit 1
fi
echo "[*] Downloading ${GGUF_NAME} from ${REPO_ID} ..."
DEST_DIR="$(dirname "${GGUF_PATH}")"
mkdir -p "${DEST_DIR}"
case "${HF}" in
hf) hf download "${REPO_ID}" "${GGUF_NAME}" --local-dir "${DEST_DIR}" ;;
huggingface-cli) huggingface-cli download "${REPO_ID}" "${GGUF_NAME}" --local-dir "${DEST_DIR}" ;;
esac
fi
if [[ ! -f "${GGUF_PATH}" ]]; then
echo "[!] GGUF still not present at ${GGUF_PATH} after download attempt." >&2
exit 1
fi
# ---- 3. Patch the Modelfile FROM line in a temp copy -------------------------
TMP_MODELFILE="$(mktemp -t thanatos27b-modelfile.XXXXXX)"
trap 'rm -f "${TMP_MODELFILE}"' EXIT
awk -v p="${GGUF_PATH}" '
/^FROM[[:space:]]/ && !done { print "FROM " p; done=1; next }
{ print }
' "${MODELFILE}" > "${TMP_MODELFILE}"
# ---- 4. Create the Ollama model ---------------------------------------------
echo "[*] ollama create ${TAG} -f <patched modelfile>"
ollama create "${TAG}" -f "${TMP_MODELFILE}"
echo
echo "[+] Done. Try it:"
echo " ollama run ${TAG}"
echo " python ${ROOT}/examples/ollama_chat.py # update MODEL constant if not 'thanatos-27b'"
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