Image-Text-to-Text
Transformers
GGUF
qwen36
Mixture of Experts
conversational
multimodal
agent
heretic
uncensored
reasoning
distillation
Instructions to use FoolDev/Janus-35B-HERETIC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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
- Pi
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
- OpenClaw new
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"
- 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
File size: 8,076 Bytes
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"""
Janus-35B — verify Modelfile and HF Ollama bridge files stay in sync.
The repo ships two parallel Ollama configurations:
- ``Modelfile`` is consumed by the local-build path
(``ollama create janus -f Modelfile``). It contains
``TEMPLATE`` / ``SYSTEM`` / ``PARAMETER`` directives.
- ``template`` / ``system`` / ``params`` at the repo root are consumed by HF's
Ollama bridge when users ``ollama run hf.co/FoolDev/Janus-35B-HERETIC`` directly. HF
does NOT read the Modelfile (per https://huggingface.co/docs/hub/en/ollama).
If the two configurations drift apart, ``hf.co/...`` users and local-build
users get different behaviour — exactly the bug fixed in commit 70ccef1
("Add HF Ollama bridge files (template/system/params)"). This script is
the regression guard: it parses the Modelfile, loads the three bridge
files, and fails on any mismatch.
Usage:
python3 scripts/check_bridge_sync.py
# exit 0 if in sync, 1 (with diff details) if not.
Run this manually before pushing a Modelfile / bridge-file edit. The 27B
sibling repo wires an equivalent script into scripts/check.sh and a
pre-commit hook; this repo intentionally stays leaner and runs it
on demand.
"""
from __future__ import annotations
import ast
import json
import re
import sys
from pathlib import Path
ROOT = Path(__file__).resolve().parent.parent
# Ollama Modelfile reference: https://docs.ollama.com/modelfile
TEMPLATE_RE = re.compile(r'^TEMPLATE\s+"""(.*?)"""', re.DOTALL | re.MULTILINE)
SYSTEM_RE = re.compile(r'^SYSTEM\s+"""(.*?)"""', re.DOTALL | re.MULTILINE)
PARAMETER_RE = re.compile(r'^PARAMETER\s+(\S+)\s+(.*?)\s*$', re.MULTILINE)
def parse_modelfile(text: str) -> tuple[str, str, dict[str, object]]:
"""Extract TEMPLATE, SYSTEM, and PARAMETER blocks from a Modelfile."""
tpl_match = TEMPLATE_RE.search(text)
if not tpl_match:
die("Modelfile has no TEMPLATE block")
template = tpl_match.group(1)
sys_match = SYSTEM_RE.search(text)
if not sys_match:
die("Modelfile has no SYSTEM block")
system = sys_match.group(1)
params: dict[str, object] = {}
stops: list[str] = []
for key, raw in PARAMETER_RE.findall(text):
# Strip outer quotes if present.
value: object = raw.strip()
if isinstance(value, str) and len(value) >= 2 and value[0] == value[-1] == '"':
value = value[1:-1]
# Stop tokens accumulate; everything else is scalar.
if key == "stop":
stops.append(value) # type: ignore[arg-type]
continue
# Cast anything numeric so it compares equal to the JSON-parsed
# bridge value (int() then float() mirrors json.loads). A key
# whitelist would leave any new numeric param a str and trip a
# false "params drift" against its JSON number.
try:
value = int(value) # type: ignore[arg-type]
except (TypeError, ValueError):
try:
value = float(value) # type: ignore[arg-type]
except (TypeError, ValueError):
pass
params[key] = value
if stops:
params["stop"] = stops
return template, system, params
def die(msg: str) -> None:
print(f"[FAIL] {msg}", file=sys.stderr)
sys.exit(1)
def diff_strings(label: str, expected: str, actual: str) -> bool:
if expected == actual:
return True
print(f"[FAIL] {label} drift detected", file=sys.stderr)
print(f" Modelfile len={len(expected)} bridge file len={len(actual)}", file=sys.stderr)
# Show the first diverging line for quick orientation.
e_lines = expected.splitlines()
a_lines = actual.splitlines()
for i, (e, a) in enumerate(zip(e_lines, a_lines)):
if e != a:
print(f" first diff at line {i + 1}:", file=sys.stderr)
print(f" modelfile : {e!r}", file=sys.stderr)
print(f" bridge : {a!r}", file=sys.stderr)
return False
if len(e_lines) != len(a_lines):
print(f" line count differs: modelfile={len(e_lines)} bridge={len(a_lines)}",
file=sys.stderr)
return False
def check_examples_system_sync(canonical_system: str) -> bool:
"""Every non-vision examples/*.py that embeds a ``*_SYSTEM`` prompt
constant must match the root ``system`` file verbatim (outer whitespace
ignored).
Guards against a text example client silently drifting from the shipped
system prompt. The vision client is skipped below — it deliberately uses
its own image-specific prompt.
"""
examples = ROOT / "examples"
if not examples.is_dir():
return True
want = canonical_system.strip()
ok = True
for path in sorted(examples.glob("*.py")):
# The vision client uses a deliberately image-specific system prompt,
# not the shared general-assistant one — exclude it from this check.
if "vision" in path.name:
continue
tree = ast.parse(path.read_text())
for node in ast.walk(tree):
if not isinstance(node, ast.Assign):
continue
names = [t.id for t in node.targets if isinstance(t, ast.Name)]
if not any(n.endswith("_SYSTEM") for n in names):
continue
try:
value = ast.literal_eval(node.value)
except (ValueError, SyntaxError):
continue
if not isinstance(value, str) or value.strip() == want:
continue
print(f"[FAIL] examples/{path.name}: {'/'.join(names)} drifted "
f"from root `system`", file=sys.stderr)
for i, (w, a) in enumerate(zip(want.splitlines(),
value.strip().splitlines())):
if w != a:
print(f" first diff at line {i + 1}:", file=sys.stderr)
print(f" system : {w!r}", file=sys.stderr)
print(f" example : {a!r}", file=sys.stderr)
break
ok = False
return ok
def main() -> int:
modelfile = (ROOT / "Modelfile").read_text()
bridge_template = (ROOT / "template").read_text()
bridge_system = (ROOT / "system").read_text()
bridge_params = json.loads((ROOT / "params").read_text())
mf_template, mf_system, mf_params = parse_modelfile(modelfile)
ok = True
# 1. TEMPLATE: byte-for-byte.
ok &= diff_strings("TEMPLATE", mf_template, bridge_template)
# 2. SYSTEM: trim trailing whitespace on both ends. The bridge file
# typically has a trailing newline; the Modelfile block doesn't.
ok &= diff_strings("SYSTEM", mf_system.strip(), bridge_system.strip())
# 3. PARAMETER vs params JSON: compare normalized dicts.
if mf_params != bridge_params:
print("[FAIL] params drift detected", file=sys.stderr)
for k in sorted(set(mf_params) | set(bridge_params)):
mv = mf_params.get(k, "<missing>")
bv = bridge_params.get(k, "<missing>")
if mv != bv:
print(f" {k}: modelfile={mv!r} bridge={bv!r}", file=sys.stderr)
ok = False
if not ok:
print("\n[!] Modelfile and bridge files are out of sync.", file=sys.stderr)
print(" Edit them together: any change to TEMPLATE / SYSTEM /",
file=sys.stderr)
print(" PARAMETER must be reflected in template / system / params.",
file=sys.stderr)
# 4. examples/*.py *_SYSTEM constants must match the root `system` file.
examples_ok = check_examples_system_sync(bridge_system)
if not examples_ok:
print("\n[!] An examples/ client's system prompt drifted from `system`.",
file=sys.stderr)
print(" Update the *_SYSTEM constant to match the root `system` "
"verbatim.", file=sys.stderr)
if not (ok and examples_ok):
return 1
print("[ ok ] Modelfile <-> bridge files + examples in sync")
return 0
if __name__ == "__main__":
sys.exit(main())
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