How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ordlibrary/hauhau-qwen36-uncensored"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ordlibrary/hauhau-qwen36-uncensored",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/ordlibrary/hauhau-qwen36-uncensored:IQ2_M
Quick Links

Hauhau Qwen3.6 — Uncensored Aggressive IQ2

ordlibrary/hauhau-qwen36-uncensored

The raw HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive GGUF (IQ2_M) without any constitutional system prompt. Same 11.7 GB IQ2_M file, zero runtime constraints.

Property Value
Architecture Qwen3.6 (35B total, ~3B active per token via MoE)
Quantization IQ2_M
Size 11 GB
Context Native 262K tokens, recommended 8K minimum
Runtime llama.cpp / llama-cpp-python / Ollama
System Prompt None — bare model, no constitution

Quick Start

Ollama

ollama run hf.co/ordlibrary/hauhau-qwen36-uncensored

llama.cpp

./llama-cli -m Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive-IQ2_M.gguf \
  --temp 0.6 --ctx-size 8192

Python (llama-cpp-python)

pip install llama-cpp-python
from llama_cpp import Llama

llm = Llama(
    model_path="Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive-IQ2_M.gguf",
    n_ctx=8192,
    verbose=False
)

output = llm("What's your take on Solana memecoins?", max_tokens=512)
print(output["choices"][0]["text"])

Modelfile (Ollama)

FROM Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive-IQ2_M.gguf

TEMPLATE """{{- if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{- if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
{{ .Response }}"""

PARAMETER num_ctx 8192
PARAMETER temperature 0.7
PARAMETER top_p 0.95
PARAMETER stop "<|im_end|>"
PARAMETER stop "<|endoftext|>"

Contrast with the Onchain Edition

Variant System Prompt Use Case
ordlibrary/hauhau-qwen36-onchain Full Onchain Constitution (20 articles) Sovereign agent, verifiable inference
ordlibrary/hauhau-qwen36-uncensored None Raw model — no guardrails, full aggression

Source

Downloads last month
445
GGUF
Model size
35B params
Architecture
qwen35moe
Hardware compatibility
Log In to add your hardware

2-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for ordlibrary/hauhau-qwen36-uncensored