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
| # 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'" | |