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: 8,649 Bytes
d87bc64 7197abd 5426482 ac94e67 d87bc64 7197abd 5426482 ac94e67 5426482 d87bc64 5426482 7197abd d87bc64 5426482 d87bc64 7197abd d87bc64 7197abd d87bc64 7197abd d87bc64 385ed94 d87bc64 7197abd d87bc64 aaef90f d87bc64 aaef90f d87bc64 aaef90f d87bc64 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 | #!/usr/bin/env bash
# Thanatos-27B β heal a previously pulled HF-bridge tag whose bundled
# GGUF is `qwen36`-stamped (legacy v0.6.0-era pulls before `964e418`,
# 3rd-round-trip-era pulls between `973d7ef` and `978798f`, or
# 5th-round-trip-era pulls between `ae67ed1` and `e03e10e`).
#
# Fresh pulls of `ollama run hf.co/FoolDev/Thanatos-27B` now get the
# qwen35-stamped bundle and load directly β this script is the
# recovery path for users who pulled a qwen36-stamped blob into
# their local Ollama store during one of the qwen36 windows
# and haven't refreshed since.
#
# It rebadges the HF-bridge tag's model blob in-place (qwen36 ->
# qwen35, metadata-only, byte-identical tensors) and rewrites the
# manifest's model-layer digest to point at the new blob. After
# running, the cached `hf.co/FoolDev/Thanatos-27B` tag loads.
#
# Idempotent: a tag already on qwen35 / qwen35moe is left untouched.
# The current bundle is qwen35-stamped so this script is a no-op for
# anyone who pulled after the latest re-stamp; it stays in the repo
# for the legacy recovery case.
#
# Usage:
# ./scripts/heal_hf_pull.sh # default tag
# TAG=hf.co/FoolDev/Thanatos-27B:Q4_K_M ./scripts/heal_hf_pull.sh
#
# Requires: ollama, jq, python3 with the `gguf` package, sha256sum.
set -euo pipefail
ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
TAG="${TAG:-hf.co/FoolDev/Thanatos-27B:Q4_K_M}"
OLLAMA_MODELS="${OLLAMA_MODELS:-${HOME}/.ollama/models}"
red() { printf "\033[31m%s\033[0m\n" "$*"; }
green() { printf "\033[32m%s\033[0m\n" "$*"; }
blue() { printf "\033[34m%s\033[0m\n" "$*"; }
blue "[*] tag: ${TAG}"
blue "[*] store: ${OLLAMA_MODELS}"
# ---- 1. Sanity ---------------------------------------------------------------
for bin in ollama jq python3 sha256sum; do
if ! command -v "${bin}" >/dev/null 2>&1; then
red "[!] missing dependency: ${bin}"; exit 1
fi
done
# ---- 2. Locate the model blob and manifest ----------------------------------
# `ollama show --modelfile` writes a FROM line with the absolute blob path.
# Reliable regardless of which case variant the user pulled with
# (hf.co's 307 lets `Thanatos-27B` and `thanatos-27b` both resolve to the
# canonical repo, and ollama stores the manifest under whichever case
# was first registered).
#
# The `if MODELFILE_OUT=...; then` form rather than a direct command
# substitution is load-bearing: under `set -e + pipefail`, a bare
# `MODEL_BLOB="$(ollama show ... | awk ...)"` silently terminates
# the script when the tag isn't pulled (ollama show exits non-zero
# -> pipefail propagates -> set -e exits the script before the
# explicit `[[ -z "${MODEL_BLOB}" ]]` check below ever runs). The
# `if` form takes the false branch on failure without tripping
# set -e, so the user gets the actionable error instead of a silent
# `make: *** [Makefile:N: heal-hf] Error 1`.
MODEL_BLOB=""
if MODELFILE_OUT="$(ollama show --modelfile "${TAG}" 2>/dev/null)"; then
MODEL_BLOB="$(awk '/^FROM[[:space:]]/ {print $2; exit}' <<<"${MODELFILE_OUT}")"
fi
if [[ -z "${MODEL_BLOB}" || ! -f "${MODEL_BLOB}" ]]; then
red "[!] could not resolve model blob for tag '${TAG}'."
red " Is the tag pulled? Try: ollama pull ${TAG}"
exit 1
fi
MODEL_HASH="$(basename "${MODEL_BLOB}" | sed 's/^sha256-//')"
blue "[*] blob: ${MODEL_BLOB}"
# Find the manifest by grepping for the model digest. The blob is
# referenced from exactly one tag in the heal scenario β fresh HF pull
# of a single :Q4_K_M tag β but if someone has multiple tags pointing
# at the same blob, we filter down to the one matching ${TAG}.
TAG_PATH="${TAG#hf.co/}" # FoolDev/Thanatos-27B:Q4_K_M
NAMESPACE_PATH="${TAG_PATH%:*}" # FoolDev/Thanatos-27B
TAG_FILE="${TAG_PATH##*:}" # Q4_K_M
MANIFEST="$(find "${OLLAMA_MODELS}/manifests/hf.co" \
-type f \
-ipath "*/${NAMESPACE_PATH}/${TAG_FILE}" 2>/dev/null | head -1)"
if [[ -z "${MANIFEST}" || ! -f "${MANIFEST}" ]]; then
red "[!] manifest not found under ${OLLAMA_MODELS}/manifests/hf.co for tag '${TAG}'."
exit 1
fi
blue "[*] manifest: ${MANIFEST}"
# ---- 3. Inspect arch ---------------------------------------------------------
ARCH="$(python3 - "${MODEL_BLOB}" <<'PY'
import sys
from gguf import GGUFReader, constants
r = GGUFReader(sys.argv[1], "r")
f = r.get_field(constants.Keys.General.ARCHITECTURE)
print(bytes(f.parts[f.data[0]]).decode())
PY
)"
blue "[*] arch: ${ARCH}"
if [[ "${ARCH}" == "qwen35" || "${ARCH}" == "qwen35moe" ]]; then
green "[=] already on a loadable arch (${ARCH}) β nothing to heal."
exit 0
fi
if [[ "${ARCH}" != "qwen36" ]]; then
red "[!] unexpected arch '${ARCH}' β refusing to heal. Edit this script if intentional."
exit 1
fi
# ---- 4. Rebadge to a temp blob and stage it in the store --------------------
# Stage in the repo's .cache/ rather than /tmp: the rebadged copy is the same
# size as the original (~17 GB), which blows past a typical tmpfs /tmp budget.
# .cache/ is on the same filesystem as ~/.ollama on a normal Linux home dir
# layout, so the final move into blobs/ is an atomic rename, not a copy.
SCRATCH_DIR="${ROOT}/.cache"
mkdir -p "${SCRATCH_DIR}"
TMP_BLOB="$(mktemp -p "${SCRATCH_DIR}" thanatos-heal.XXXXXX.gguf)"
trap 'rm -f "${TMP_BLOB}"' EXIT
blue "[*] rebadging qwen36 -> qwen35 (metadata only, tensors byte-identical) ..."
python3 "${ROOT}/scripts/rename_arch.py" \
--from-arch qwen36 --to-arch qwen35 \
"${MODEL_BLOB}" "${TMP_BLOB}"
NEW_HASH="$(sha256sum "${TMP_BLOB}" | awk '{print $1}')"
NEW_SIZE="$(stat -c '%s' "${TMP_BLOB}")"
NEW_BLOB="${OLLAMA_MODELS}/blobs/sha256-${NEW_HASH}"
blue "[*] new digest: sha256:${NEW_HASH}"
blue "[*] new size: ${NEW_SIZE}"
if [[ -f "${NEW_BLOB}" ]]; then
blue "[=] target blob already in store β reusing."
rm -f "${TMP_BLOB}"
else
mv "${TMP_BLOB}" "${NEW_BLOB}"
fi
trap - EXIT
# ---- 5. Rewrite the manifest's model layer ----------------------------------
# Keep a sidecar copy of the original manifest so we can roll back if
# `ollama show` rejects the rewrite. The blob cleanup in step 7 only
# happens AFTER validation passes, so a rollback always lands on a
# consistent (original manifest, original blob still present) state.
BACKUP_MANIFEST="${MANIFEST}.heal-backup"
cp "${MANIFEST}" "${BACKUP_MANIFEST}"
TMP_MANIFEST="$(mktemp -t thanatos-heal-manifest.XXXXXX.json)"
trap 'rm -f "${TMP_MANIFEST}"' EXIT
jq --arg new "sha256:${NEW_HASH}" \
--argjson size "${NEW_SIZE}" '
.layers |= map(
if .mediaType == "application/vnd.ollama.image.model"
then .digest = $new | .size = $size
else .
end
)
' "${MANIFEST}" > "${TMP_MANIFEST}"
NEW_DIGEST_IN_MANIFEST="$(jq -r '
.layers[] | select(.mediaType == "application/vnd.ollama.image.model") | .digest
' "${TMP_MANIFEST}")"
if [[ "${NEW_DIGEST_IN_MANIFEST}" != "sha256:${NEW_HASH}" ]]; then
red "[!] manifest rewrite failed (digest mismatch); not committing."
rm -f "${BACKUP_MANIFEST}"
exit 1
fi
mv "${TMP_MANIFEST}" "${MANIFEST}"
trap - EXIT
# ---- 6. Validate the rewritten manifest via ollama show ---------------------
# `ollama show` parses the manifest, walks the layer digests, and reads
# enough of the model blob to extract metadata (arch, params, etc.).
# A buggy rewrite that produces jq-accepted JSON but breaks an ollama
# invariant (layer order, mediaType set, digest-vs-blob-bytes
# mismatch) trips here, before we lose the rollback path by removing
# the old qwen36 blob. On failure we restore from BACKUP_MANIFEST.
blue "[*] validating rewritten manifest with 'ollama show'..."
if ! ollama show "${TAG}" >/dev/null 2>&1; then
red "[!] ollama show ${TAG} failed after the manifest rewrite."
blue "[*] rolling back: restoring original manifest from ${BACKUP_MANIFEST}"
mv "${BACKUP_MANIFEST}" "${MANIFEST}"
red " Tag is back to its pre-heal (qwen36) state. The new qwen35"
red " blob is left in the store; ollama auto-prunes unreferenced"
red " blobs on next restart."
exit 1
fi
rm -f "${BACKUP_MANIFEST}"
green "[+] manifest validates."
# ---- 7. Remove the old qwen36 blob if no other manifest references it -------
OLD_DIGEST="sha256:${MODEL_HASH}"
if ! grep -rlF -- "${OLD_DIGEST}" "${OLLAMA_MODELS}/manifests/" >/dev/null 2>&1; then
blue "[*] no other manifest references the old qwen36 blob β removing ${MODEL_BLOB}"
rm -f "${MODEL_BLOB}"
else
blue "[=] old qwen36 blob still referenced by another manifest β leaving in place."
fi
echo
green "[+] healed. Try it:"
echo " ollama run ${TAG}"
echo " MODEL=${TAG} make smoke"
|