Instructions to use brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use brainnxdomain/Astrea-R8-Chat-9B-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 brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf brainnxdomain/Astrea-R8-Chat-9B-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 brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf brainnxdomain/Astrea-R8-Chat-9B-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 brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf brainnxdomain/Astrea-R8-Chat-9B-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 brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF:Q4_K_M
Use Docker
docker model run hf.co/brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF with Ollama:
ollama run hf.co/brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF:Q4_K_M
- Unsloth Studio
How to use brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF 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 brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF 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 brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF to start chatting
- Pi
How to use brainnxdomain/Astrea-R8-Chat-9B-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 brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF: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": "brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use brainnxdomain/Astrea-R8-Chat-9B-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 brainnxdomain/Astrea-R8-Chat-9B-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 brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use brainnxdomain/Astrea-R8-Chat-9B-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 brainnxdomain/Astrea-R8-Chat-9B-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 "brainnxdomain/Astrea-R8-Chat-9B-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"
- Docker Model Runner
How to use brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF with Docker Model Runner:
docker model run hf.co/brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF:Q4_K_M
- Lemonade
How to use brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull brainnxdomain/Astrea-R8-Chat-9B-Heretic-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Astrea-R8-Chat-9B-Heretic-GGUF-Q4_K_M
List all available models
lemonade list
- Astrea-R8-Chat-9B-Heretic-T32-GGUF
Astrea-R8-Chat-9B-Heretic-T32-GGUF
GGUF conversions of Altworld/Astrea-R8-Chat-9B, modified using the Heretic automated directional-ablation process.
This release is based on Heretic and includes several quantization levels for use with llama.cpp, LM Studio, KoboldCpp, and other GGUF-compatible runtimes.
The model retains its original multimodal architecture. Vision use requires the separate matching mmproj file included in this repository.
Model details
| Property | Value |
|---|---|
| Base model | Altworld/Astrea-R8-Chat-9B |
| Parameter class | Approximately 9B |
| Modification | Heretic automated directional ablation |
| Selected candidate | KL divergence: 0.0316, Refusals: 8/100 |
| Format | GGUF |
| Text runtime | llama.cpp-compatible |
| Vision support | Yes, with matching mmproj |
| Context metadata | 262,144 tokens |
| MTP included | No |
| Primary precision | BF16 |
| Quantizations | Q8_0, Q6_K, Q5_K_M, Q4_K_M, Q4_K_S |
Practical context length depends on available memory, runtime configuration, and workload. A smaller context such as 8,192 or 16,384 tokens is a reasonable starting point for local use.
What was changed?
The source model was processed using p-e-w/heretic, which applies optimized directional ablation—sometimes called abliteration—to reduce learned refusal behavior.
Heretic searches for ablation parameters that reduce refusals while minimizing divergence from the original model. This is not a conventional supervised fine-tune, LoRA, merge, or prompt modification.
This release uses the output selected as KL divergence: 0.0316, Refusals: 8/100.
The language-model weights were modified. The vision encoder and multimodal projector were not intentionally ablated.
Important MTP note
The source configuration declared an additional Multi-Token Prediction or NextN layer, but the saved checkpoint did not contain the associated MTP tensors.
Including that declaration caused affected llama.cpp builds to expect a nonexistent tensor:
blk.32.attn_norm.weight
The language-model GGUFs in this repository were therefore exported with:
--no-mtp
This excludes the unavailable MTP head. It does not remove normal text generation, chat, reasoning, or vision capabilities.
Available files
| File | Intended use |
|---|---|
Astrea-R8-Chat-9B-Heretic-T32-BF16.gguf |
Archival master and maximum weight fidelity |
Astrea-R8-Chat-9B-Heretic-T32-Q8_0.gguf |
Very high quality; near-BF16 practical version |
Astrea-R8-Chat-9B-Heretic-T32-Q6_K.gguf |
High-quality local inference |
Astrea-R8-Chat-9B-Heretic-T32-Q5_K_M.gguf |
Strong quality-to-size balance |
Astrea-R8-Chat-9B-Heretic-T32-Q4_K_M.gguf |
Recommended compact version |
Astrea-R8-Chat-9B-Heretic-T32-Q4_K_S.gguf |
Smaller mainstream quant |
mmproj-Astrea-R8-Chat-9B-Heretic-T32-BF16.gguf |
Maximum-quality vision encoder/projector |
mmproj-Astrea-R8-Chat-9B-Heretic-T32-Q8_0.gguf |
Recommended vision encoder/projector |
Actual filenames may differ slightly depending on the final files uploaded to this repository.
Quantization recommendations
Best overall compact version
Q4_K_M language model
Q8_0 mmproj
Better text quality
Q5_K_M or Q6_K language model
Q8_0 mmproj
Maximum practical quality
Q8_0 language model
Q8_0 or BF16 mmproj
Archival/reference version
BF16 language model
BF16 mmproj
The mmproj is much smaller than the language model and directly affects visual understanding. Q8_0 or BF16 is recommended for the projector rather than aggressively quantizing it.
Text-only usage with llama.cpp
llama-cli \
-m Astrea-R8-Chat-9B-Heretic-T32-Q4_K_M.gguf \
-ngl 999 \
-c 8192 \
-n 512 \
-cnv
For a one-shot prompt:
llama-cli \
-m Astrea-R8-Chat-9B-Heretic-T32-Q4_K_M.gguf \
-ngl 999 \
-c 8192 \
-n 512 \
-p "Explain why the sky appears blue."
On Windows CMD, place the command on one line or use ^ instead of \ for line continuation.
Vision usage with llama.cpp
Vision requires both the language-model GGUF and the matching mmproj:
llama-cli \
-m Astrea-R8-Chat-9B-Heretic-T32-Q4_K_M.gguf \
--mmproj mmproj-Astrea-R8-Chat-9B-Heretic-T32-Q8_0.gguf \
--image example.jpg \
-ngl 999 \
-c 8192 \
-n 512 \
-p "Describe this image in detail."
You may also use the dedicated multimodal test utility:
llama-mtmd-cli \
-m Astrea-R8-Chat-9B-Heretic-T32-Q4_K_M.gguf \
--mmproj mmproj-Astrea-R8-Chat-9B-Heretic-T32-Q8_0.gguf \
--image example.jpg \
-ngl 999 \
-c 8192 \
-p "Describe this image."
Server usage
Text and vision can be exposed through llama.cpp’s OpenAI-compatible server:
llama-server \
-m Astrea-R8-Chat-9B-Heretic-T32-Q4_K_M.gguf \
--mmproj mmproj-Astrea-R8-Chat-9B-Heretic-T32-Q8_0.gguf \
-ngl 999 \
-c 8192 \
--host 0.0.0.0 \
--port 8080
Omit --mmproj when only text generation is needed.
Binding to 0.0.0.0 exposes the server to the local network. Use appropriate firewall rules and authentication controls before exposing it beyond a trusted network.
Chat template
The model’s embedded chat template was preserved during conversion.
GGUF-compatible applications should normally detect and use the embedded template automatically. Avoid manually selecting an unrelated Qwen template unless your runtime fails to detect it.
Evaluation
This release has not yet been subjected to a comprehensive independent benchmark suite.
The selected Heretic candidate was chosen from the automated optimization process, but that should not be treated as evidence of performance on general reasoning, coding, multilingual, multimodal, or safety benchmarks.
Suggested evaluations include:
- Comparison against the unmodified source model
- KL-divergence or perplexity comparison
- Instruction-following tests
- Refusal-rate testing
- General reasoning and coding tasks
- Vision-question answering
- OCR and detailed image-description tests
- Long-context retrieval
- Quantization comparisons across Q4_K_S through Q8_0
Community benchmark results and reproducible test reports are welcome.
Intended use
This model is intended for:
- Local experimentation
- Research into directional ablation and refusal behavior
- General conversational use
- Creative writing
- Coding and technical assistance
- Multimodal image understanding
- Comparing quantization formats
- Evaluating alignment and behavioral changes
Limitations
Directional ablation can change behavior in ways that are not fully captured by refusal-rate or divergence measurements.
Possible limitations include:
- Reduced safety refusals
- Harmful, offensive, misleading, or inappropriate output
- Incorrect factual claims
- Overconfidence
- Degraded behavior on prompts unlike those used during optimization
- Differences between quantization levels
- Reduced visual accuracy when using a quantized projector
- Inconsistent tool-call or structured-output behavior
- High memory use at very long context lengths
The absence of a refusal does not mean a response is correct, safe, legal, or appropriate.
Users are responsible for evaluating the model for their own application and implementing any safeguards required for that application.
Safety notice
This is a deliberately less-restricted model.
It may comply with requests that the upstream model would decline, and it may generate content that is inaccurate, offensive, unsafe, or unsuitable for deployment without additional controls.
Do not rely on the model as the sole source of medical, legal, financial, security, or other high-stakes advice.
Reproducibility
The language model was converted from the selected Heretic output using llama.cpp.
Representative BF16 conversion:
python convert_hf_to_gguf.py PATH_TO_HERETIC_OUTPUT \
--no-mtp \
--outfile Astrea-R8-Chat-9B-Heretic-T32-BF16-noMTP.gguf \
--outtype bf16
Representative direct Q8_0 conversion:
python convert_hf_to_gguf.py PATH_TO_HERETIC_OUTPUT \
--no-mtp \
--outfile Astrea-R8-Chat-9B-Heretic-T32-Q8_0.gguf \
--outtype q8_0
Representative Q4_K_M quantization from BF16:
llama-quantize \
Astrea-R8-Chat-9B-Heretic-T32-BF16-noMTP.gguf \
Astrea-R8-Chat-9B-Heretic-T32-Q4_K_M.gguf \
Q4_K_M
Representative Q8_0 mmproj conversion:
python convert_hf_to_gguf.py PATH_TO_HERETIC_OUTPUT \
--mmproj \
--outfile Astrea-R8-Chat-9B-Heretic-T32-Q8_0.gguf \
--outtype q8_0
The converter automatically adds the mmproj- filename prefix when exporting a multimodal projector.
All lower-precision language-model quants should be generated independently from the BF16 master rather than from another quantized file.
Credits
- Original model:
Altworld/Astrea-R8-Chat-9B - Underlying architecture: Qwen3.5
- Directional-ablation tooling:
p-e-w/heretic - GGUF conversion and runtime:
ggml-org/llama.cpp
This repository distributes a modified and quantized derivative. It does not claim authorship of the original model, architecture, training data, or the Heretic and llama.cpp tooling.
License
This repository is licensed under the Apache License 2.0, following the license of the upstream model.
This is a modified derivative of:
- Altworld/Astrea-R8-Chat-9B
- Qwen/Qwen3.5-9B
The modifications, GGUF conversion, and quantization performed for this repository do not imply endorsement by the original model authors.
See the included LICENSE file for the complete license terms.
Disclaimer
This model is provided without warranties. The uploader is not responsible for outputs produced by the model or for downstream uses by third parties.
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