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 Claude Opus 4.7 commited on 11 days ago

Commit

c336f44

1 Parent(s): 7063e20

docs(examples): wire heal-hf into the Ollama setup path

Browse files

`examples/README.md`'s "easiest path" told users to `ollama pull
hf.co/FoolDev/Thanatos-27B` then run `ollama_chat.py` against the
pulled tag. That path is broken today: the pull succeeds, but the
first inference call returns the qwen36 500 (`unable to load
model: <blob>`) because the bundle is qwen36-stamped — exactly the
failure mode `make heal-hf` now repairs.

Section rewritten:

- Lead with the pull + `cd .. && make heal-hf && cd examples`
recovery (one extra command after pull, rebadges the pulled
blob in store so the same `hf.co/...` tag becomes loadable).
- Add the `make load-bundle` alternative that bypasses the HF pull
entirely by loading this repo's bundled GGUF directly and
building a local `thanatos-27b` tag — relevant for users who'd
rather not heal-after-pull.
- Add the `make build QUANT=...` alternative for non-bundled quants
(Q3_K_S, Q5_K_M, etc.) that downloads from
`unsloth/Qwen3.6-27B-GGUF` (qwen35-stamped, loads today) and
builds the same local tag.

All three paths set MODEL explicitly so `ollama_chat.py` runs
against the correct tag (`hf.co/...` for the heal path,
`thanatos-27b` for the load-bundle / build paths).

Closes the last user-facing place where the heal-hf workaround
wasn't documented — main README, Architecture, Quick start, and now
examples/README all point at it.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

Files changed (2) hide show

CHANGELOG.md +11 -0
examples/README.md +22 -6

CHANGELOG.md CHANGED Viewed

@@ -44,6 +44,17 @@ and documentation**, not the underlying base model.
   README warns about. Modelfile hardware notes updated.
 ### Changed
 - README "Architecture" section + Quick start option A:
   - Architecture body now notes that neither `ggml-org/llama.cpp`
     nor `ollama/ollama` has an open PR or tracking issue for a

   README warns about. Modelfile hardware notes updated.
 ### Changed
+- `examples/README.md` Ollama setup section: the previous "easiest
+  path" told users to `ollama pull hf.co/FoolDev/Thanatos-27B` then
+  run `ollama_chat.py` against the pulled tag — which fails today
+  because the bundle is qwen36-stamped (the pull succeeds; the
+  first inference call returns the qwen36 500). Section rewritten
+  to lead with the pull + `make heal-hf` recovery (one extra
+  command after pull, rebadges the blob in place so the same
+  `hf.co/...` tag loads), and adds the `make load-bundle` /
+  `make build QUANT=...` alternatives as the bypass-the-bundle
+  paths that don't touch the HF pull at all. All three set MODEL
+  explicitly so the right tag is used.
 - README "Architecture" section + Quick start option A:
   - Architecture body now notes that neither `ggml-org/llama.cpp`
     nor `ollama/ollama` has an open PR or tracking issue for a

examples/README.md CHANGED Viewed

@@ -19,11 +19,16 @@ from the `Modelfile` / bridge files.
 ### Ollama
-Easiest path — pull straight from HF (gets the bundled Q4_K_M GGUF +
-this repo's Modelfile in one step):
 ```bash
 ollama pull hf.co/FoolDev/Thanatos-27B           # 17 GB Q4_K_M (only bundled quant)
 pip install requests
 MODEL=hf.co/FoolDev/Thanatos-27B python ollama_chat.py
 ```
@@ -31,12 +36,23 @@ MODEL=hf.co/FoolDev/Thanatos-27B python ollama_chat.py
 For the smaller-footprint Q3_K_S (~12 GB) or other quants, build
 locally instead — see the parent repo's `make build QUANT=...` flow.
-Or build locally from this repo (uses the bundled `Thanatos-27B.Q4_K_M.gguf`,
-no edits required):
 ```bash
-cd ..  &&  make build  &&  cd examples
-python ollama_chat.py
 ```
 For a quant the repo doesn't bundle (e.g. Q5_K_M), `make build` will

 ### Ollama
+Pull straight from HF (gets the bundled Q4_K_M GGUF + this repo's
+root-level `template` / `system` / `params` files via HF's Ollama
+bridge), then heal the bundle's `qwen36` arch stamp so Ollama can
+actually load it. The pull itself succeeds; the first inference
+fails with `unable to load model` until heal — see parent README's
+[Architecture](../README.md#architecture) for why:
 ```bash
 ollama pull hf.co/FoolDev/Thanatos-27B           # 17 GB Q4_K_M (only bundled quant)
+cd ..  &&  make heal-hf  &&  cd examples         # rebadges the pulled blob qwen36 -> qwen35 in store
 pip install requests
 MODEL=hf.co/FoolDev/Thanatos-27B python ollama_chat.py
 ```
 For the smaller-footprint Q3_K_S (~12 GB) or other quants, build
 locally instead — see the parent repo's `make build QUANT=...` flow.
+Or build locally from this repo without going through the HF pull
+(uses the bundled `Thanatos-27B.Q4_K_M.gguf` via `make load-bundle`,
+which handles the qwen36 → qwen35 rebadge in one shot and creates a
+local `thanatos-27b` tag):
 ```bash
+cd ..  &&  make load-bundle  &&  cd examples
+MODEL=thanatos-27b python ollama_chat.py
+```
+For a non-bundled quant (e.g. Q5_K_M, Q3_K_S), `make build QUANT=...`
+downloads a qwen35-stamped GGUF from `unsloth/Qwen3.6-27B-GGUF` and
+creates the same local tag — bypasses the bundle and the heal entirely:
+```bash
+cd ..  &&  make build QUANT=Q5_K_M  &&  cd examples
+MODEL=thanatos-27b python ollama_chat.py
 ```
 For a quant the repo doesn't bundle (e.g. Q5_K_M), `make build` will