Instructions to use Abiray/Hemmingway-1-heretic-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Abiray/Hemmingway-1-heretic-GGUF 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 Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Abiray/Hemmingway-1-heretic-GGUF: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 Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Abiray/Hemmingway-1-heretic-GGUF: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 Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use Abiray/Hemmingway-1-heretic-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Abiray/Hemmingway-1-heretic-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Abiray/Hemmingway-1-heretic-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M

Ollama
How to use Abiray/Hemmingway-1-heretic-GGUF with Ollama:
```
ollama run hf.co/Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M
```
Unsloth Desktop

How to use Abiray/Hemmingway-1-heretic-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Abiray/Hemmingway-1-heretic-GGUF with Docker Model Runner:
```
docker model run hf.co/Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M
```

Lemonade

How to use Abiray/Hemmingway-1-heretic-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Hemmingway-1-heretic-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use Abiray/Hemmingway-1-heretic-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Abiray/Hemmingway-1-heretic-GGUF: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 Abiray/Hemmingway-1-heretic-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Abiray/Hemmingway-1-heretic-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Abiray/Hemmingway-1-heretic-GGUF: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 "Abiray/Hemmingway-1-heretic-GGUF: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"

Hemmingway-1-heretic-GGUF

This repository contains static GGUF quantizations of Hemmingway-1-heretic, created by applying the arelath/Hemmingway-1-heretic-adapter to Altworld/Hemmingway-1 (a 27B model built on Qwen3.8-27B) and quantizing for local inference with llama.cpp.

Hemmingway-1 is tuned specifically to write like a real person—skipping preambles, lecture notes, and corporate filler. This heretic version decensors the weights via targeted representation abliteration using Heretic v2.0.0, reducing refusals to near-zero while preserving high-EQ conversational voice.

Quantization Variants

Filename	Size	Recommended RAM/VRAM	Description
`Hemmingway-1-heretic-Q3_K_M.gguf`	13.5 GB	~16 GB	Maximum compression; fits on mid-range hardware with slight perplexity trade-off.
`Hemmingway-1-heretic-Q4_K_S.gguf`	15.8 GB	~19 GB	Lightweight 4-bit; fast tokens/sec for tighter memory envelopes.
`Hemmingway-1-heretic-Q4_K_M.gguf`	16.8 GB	~20 GB	Recommended balance. Retains near-full baseline accuracy with solid speed.
`Hemmingway-1-heretic-Q5_K_M.gguf`	19.5 GB	~23 GB	High fidelity; preserves subtle nuanced phrasing and tone.
`Hemmingway-1-heretic-Q6_K.gguf`	22.4 GB	~26 GB	Near loss-less reproduction of the 16-bit unquantized model.
`Hemmingway-1-heretic-Q8_0.gguf`	29.0 GB	~33 GB	Maximum quality 8-bit quantization for high-VRAM setups.

Decensoring & Abliteration Details

Created using Heretic v2.0.0.dev0 against Altworld/Hemmingway-1.

Abliteration Parameters

direction_index: 38.05
attn.o_proj.max_weight: 1.03 (position: 41.01, min_weight: 1.02, min_distance: 28.56)
mlp.down_proj.max_weight: 1.41 (position: 51.07, min_weight: 1.39, min_distance: 35.29)

Refusal Comparison

Metric	This Model (Heretic)	Original Hemmingway-1
Refusals	2 / 100	95 / 100
KL Divergence	0.1662	0 (baseline)

Quickstart & Usage

1. llama.cpp CLI

# Clone and build llama.cpp, then run:
./llama-cli \
  -m Hemmingway-1-heretic-Q4_K_M.gguf \
  -p "<|im_start|>system\nYou are a direct, empathetic writing assistant.<|im_end|>\n<|im_start|>user\nWrite the text I send my landlord about the broken boiler.<|im_end|>\n<|im_start|>assistant\n" \
  -n 512 \
  -ngl 99 \
  -c 8192

Credits & Licensing

Base Weights: Altworld/Hemmingway-1 by Altworld, built on Qwen/Qwen3.8-27B.

Abliteration Adapter: arelath/Hemmingway-1-heretic-adapter by arelath.

License: Governed by the original model's license terms: CC BY-NC 4.0 (Free for personal and non-commercial research use; commercial usage requires agreement with Altworld).

Downloads last month: -

GGUF

Model size

27B params

Architecture

qwen35

Hardware compatibility

3-bit

4-bit

5-bit

6-bit

8-bit

Model tree for Abiray/Hemmingway-1-heretic-GGUF

Base model

Qwen/Qwen3.8-27B

Finetuned

Altworld/Hemmingway-1

Quantized

(35)

this model