Instructions to use FoolDev/Thanatos-27B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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

FoolDev commited on 26 days ago

Commit

3d2e907

1 Parent(s): b20f7c9

Modelfile: point FROM at bundled Janus-27B.Q4_K_M.gguf

Browse files

The repo now ships Janus-27B.Q4_K_M.gguf and Janus-27B.Q3_K_S.gguf
(commits b0d8482 and 4c20ab5), so a fresh clone with LFS smudge on
already has a working GGUF on disk. The previous default
(./Qwen3.6-27B-Q4_K_M.gguf) was a file that didn't exist after a
clone, forcing users to either run make build or hand-edit the
Modelfile before ollama create would work.

Comment block refreshed: removed the stale 'does not redistribute
weights' line (contradicted by the bundled GGUFs) and added a
pointer to make build QUANT=Q3_K_S for the smaller quant.

scripts/build.sh keeps patching FROM in a temp Modelfile copy, so
existing make build flows are unchanged regardless of which path
the FROM points at on disk.

Files changed (2) hide show

CHANGELOG.md +12 -0
Modelfile +9 -8

CHANGELOG.md CHANGED Viewed

@@ -7,6 +7,18 @@ and documentation**, not the underlying base model.
 ## [Unreleased]
 ### Added
 - `examples/ollama_chat.py`: respect `MODEL` and `HOST` env vars
   (matches the convention scripts/smoke_test.sh and scripts/bench.sh

 ## [Unreleased]
+### Fixed
+- `Modelfile`: change FROM from `./Qwen3.6-27B-Q4_K_M.gguf` to
+  `./Janus-27B.Q4_K_M.gguf`. The repo now ships GGUFs (commit b0d8482
+  added Q4_K_M, commit 4c20ab5 added Q3_K_S), so the no-script path
+  `git clone && ollama create janus-27b -f Modelfile` works
+  out-of-the-box for users with LFS smudge enabled. Comment block
+  refreshed: removed the stale "does not redistribute weights" line
+  (contradicted by the bundled GGUFs) and added a pointer to
+  `make build QUANT=Q3_K_S` for the smaller quant. `scripts/build.sh`
+  still patches FROM in a temp Modelfile copy, so existing build
+  flows are unchanged.
 ### Added
 - `examples/ollama_chat.py`: respect `MODEL` and `HOST` env vars
   (matches the convention scripts/smoke_test.sh and scripts/bench.sh

Modelfile CHANGED Viewed

@@ -5,20 +5,21 @@
 # missing the qwen35 arch entries). Use llama.cpp directly for image
 # input, or wait for the fix. See the Vision section in README.md.
 #
-# This repo does not redistribute weights. Edit the FROM line below to
-# point at a local Qwen 3.6 27B GGUF, then:
 #
 #     ollama create janus-27b -f Modelfile && ollama run janus-27b
 #
-# Recommended GGUF source:
-#     https://huggingface.co/unsloth/Qwen3.6-27B-GGUF
 #
-# Or a community Opus-distilled variant:
 #     https://huggingface.co/rico03/Qwen3.6-27B-Claude-Opus-Reasoning-Distilled-GGUF
-#
-# Replace the path below with wherever you keep the GGUF.
-FROM ./Qwen3.6-27B-Q4_K_M.gguf
 # Chat template — Qwen 3.6 ChatML in Ollama Go-template form, with the
 # tool-calling blocks Ollama's capability detector looks for. Without a

 # missing the qwen35 arch entries). Use llama.cpp directly for image
 # input, or wait for the fix. See the Vision section in README.md.
 #
+# This repo bundles two GGUFs: Janus-27B.Q4_K_M.gguf (~17 GB, default)
+# and Janus-27B.Q3_K_S.gguf (~12 GB, smaller-footprint option). The FROM
+# line below points at the bundled Q4_K_M, so a fresh clone (with LFS
+# smudge enabled) supports the no-script path:
 #
 #     ollama create janus-27b -f Modelfile && ollama run janus-27b
 #
+# To use the smaller quant, edit FROM to ./Janus-27B.Q3_K_S.gguf, or run
+# `make build QUANT=Q3_K_S` which patches FROM in a temp Modelfile copy.
 #
+# Other GGUF sources (use with `make build GGUF_PATH=...`):
+#     https://huggingface.co/unsloth/Qwen3.6-27B-GGUF
 #     https://huggingface.co/rico03/Qwen3.6-27B-Claude-Opus-Reasoning-Distilled-GGUF
+FROM ./Janus-27B.Q4_K_M.gguf
 # Chat template — Qwen 3.6 ChatML in Ollama Go-template form, with the
 # tool-calling blocks Ollama's capability detector looks for. Without a