license: mit
language:
- en
tags: - solana
- blockchain
- onchain
- clawd
- qwen
- gguf
- uncensored
- aggressive
library_name: ggml
pipeline_tag: text-generation
base_model: HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
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
- Base: HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
- Quant: IQ2_M (11 GB)