Instructions to use FoolDev/Janus-35B-HERETIC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FoolDev/Janus-35B-HERETIC with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="FoolDev/Janus-35B-HERETIC")
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/Janus-35B-HERETIC", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use FoolDev/Janus-35B-HERETIC with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf FoolDev/Janus-35B-HERETIC:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf FoolDev/Janus-35B-HERETIC:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf FoolDev/Janus-35B-HERETIC:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf FoolDev/Janus-35B-HERETIC: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/Janus-35B-HERETIC:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf FoolDev/Janus-35B-HERETIC: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/Janus-35B-HERETIC:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf FoolDev/Janus-35B-HERETIC:Q4_K_M

Use Docker

docker model run hf.co/FoolDev/Janus-35B-HERETIC:Q4_K_M

LM Studio
Jan

vLLM

How to use FoolDev/Janus-35B-HERETIC with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FoolDev/Janus-35B-HERETIC"
# 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/Janus-35B-HERETIC",
		"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/Janus-35B-HERETIC:Q4_K_M

SGLang

How to use FoolDev/Janus-35B-HERETIC 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/Janus-35B-HERETIC" \
    --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/Janus-35B-HERETIC",
		"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/Janus-35B-HERETIC" \
        --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/Janus-35B-HERETIC",
		"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/Janus-35B-HERETIC with Ollama:
```
ollama run hf.co/FoolDev/Janus-35B-HERETIC:Q4_K_M
```

Unsloth Studio

How to use FoolDev/Janus-35B-HERETIC 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/Janus-35B-HERETIC 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/Janus-35B-HERETIC to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for FoolDev/Janus-35B-HERETIC to start chatting

How to use FoolDev/Janus-35B-HERETIC with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf FoolDev/Janus-35B-HERETIC: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/Janus-35B-HERETIC:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use FoolDev/Janus-35B-HERETIC with Docker Model Runner:
```
docker model run hf.co/FoolDev/Janus-35B-HERETIC:Q4_K_M
```

Lemonade

How to use FoolDev/Janus-35B-HERETIC with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull FoolDev/Janus-35B-HERETIC:Q4_K_M

Run and chat with the model

lemonade run user.Janus-35B-HERETIC-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use FoolDev/Janus-35B-HERETIC with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf FoolDev/Janus-35B-HERETIC: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/Janus-35B-HERETIC:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use FoolDev/Janus-35B-HERETIC with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf FoolDev/Janus-35B-HERETIC:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "FoolDev/Janus-35B-HERETIC:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

FoolDev Claude Fable 5 commited on 15 days ago

Commit

d9d9f49

1 Parent(s): 9382597

fix(load_bundle): portable LFS-pointer size probe (wc -c, not GNU stat -c)

Browse files

resolve_bundle() sized the bundle with `stat -c '%s'`, GNU-only syntax that
errors on macOS/BSD stat (which needs `-f%z`). macOS is an advertised host
(Mac Studio in the Modelfile + README), so this leaked a stderr line there;
the empty-string-to-0 coercion only happened to preserve correct routing.
`wc -c < file` is POSIX and identical on GNU and BSD.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

Files changed (2) hide show

CHANGELOG.md +5 -0
scripts/load_bundle.sh +1 -1

CHANGELOG.md CHANGED Viewed

@@ -26,6 +26,11 @@ track the **tooling and documentation**, not the underlying base model.
   override.
 ### Fixed
 - **`examples/llama_cpp_quickstart.py` system prompt restored.** Its
   `JANUS_SYSTEM` had truncated to five behavior rules (dropped "or
   meta-commentary" and "or incomplete", and omitted the creative-writing and

   override.
 ### Fixed
+- **`scripts/load_bundle.sh` LFS-pointer size check is now portable.** The
+  bundle resolver probed file size with GNU-only `stat -c '%s'`, which errors on
+  macOS/BSD `stat` (that needs `-f%z`) — leaking a stderr line on an advertised
+  supported host (the Modelfile and README list Mac Studio as a working config).
+  Switched to `wc -c`, which is identical on GNU and BSD.
 - **`examples/llama_cpp_quickstart.py` system prompt restored.** Its
   `JANUS_SYSTEM` had truncated to five behavior rules (dropped "or
   meta-commentary" and "or incomplete", and omitted the creative-writing and

scripts/load_bundle.sh CHANGED Viewed

@@ -52,7 +52,7 @@ resolve_bundle() {
     # LFS pointer files are tiny (a couple hundred bytes) and start with
     # `version https://git-lfs.github.com/spec/v1`.
     local size
-    size="$(stat -c '%s' "${file}")"
     if (( size < 1024 )) && head -n1 "${file}" | grep -q 'git-lfs'; then
         return 1
     fi

     # LFS pointer files are tiny (a couple hundred bytes) and start with
     # `version https://git-lfs.github.com/spec/v1`.
     local size
+    size="$(wc -c < "${file}")"
     if (( size < 1024 )) && head -n1 "${file}" | grep -q 'git-lfs'; then
         return 1
     fi