Instructions to use Hal0ai/hal0-brain-sft-ROCmFPX-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Hal0ai/hal0-brain-sft-ROCmFPX-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Hal0ai/hal0-brain-sft-ROCmFPX-GGUF", filename="hal0-brain-sft-F16.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Hal0ai/hal0-brain-sft-ROCmFPX-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 Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16 # Run inference directly in the terminal: llama cli -hf Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16 # Run inference directly in the terminal: llama cli -hf Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
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 Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16 # Run inference directly in the terminal: ./llama-cli -hf Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
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 Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
Use Docker
docker model run hf.co/Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
- LM Studio
- Jan
- vLLM
How to use Hal0ai/hal0-brain-sft-ROCmFPX-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Hal0ai/hal0-brain-sft-ROCmFPX-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": "Hal0ai/hal0-brain-sft-ROCmFPX-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
- Ollama
How to use Hal0ai/hal0-brain-sft-ROCmFPX-GGUF with Ollama:
ollama run hf.co/Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
- Unsloth Studio
How to use Hal0ai/hal0-brain-sft-ROCmFPX-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 Hal0ai/hal0-brain-sft-ROCmFPX-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 Hal0ai/hal0-brain-sft-ROCmFPX-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Hal0ai/hal0-brain-sft-ROCmFPX-GGUF to start chatting
- Pi
How to use Hal0ai/hal0-brain-sft-ROCmFPX-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
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": "Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Hal0ai/hal0-brain-sft-ROCmFPX-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 Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
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 Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use Hal0ai/hal0-brain-sft-ROCmFPX-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
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 "Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16" \ --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 Hal0ai/hal0-brain-sft-ROCmFPX-GGUF with Docker Model Runner:
docker model run hf.co/Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
- Lemonade
How to use Hal0ai/hal0-brain-sft-ROCmFPX-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Hal0ai/hal0-brain-sft-ROCmFPX-GGUF:F16
Run and chat with the model
lemonade run user.hal0-brain-sft-ROCmFPX-GGUF-F16
List all available models
lemonade list
File size: 7,289 Bytes
29b8461 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 | ---
license: apache-2.0
pipeline_tag: text-generation
base_model: Hal0ai/hal0-brain-sft
base_model_relation: quantized
tags:
- hal0
- hal0-brain
- gguf
- rocmfpx
- rocmfp4
- rocmfp8
- agent
- tool-use
language:
- en
---

# HAL0 BRAIN — ROCmFPX GGUF
**Advanced reasoning · Tool calling · Platform management**
HAL0 BRAIN is a mini-agent administrator trained on the hal0 system: its services, profiles, slots, model lifecycle, diagnostics, and tool workflows. This repository packages the verified F16 reference plus two agent-oriented ROCmFPX quants for structured reasoning, tool calling, and platform management.
## Files
| File | Preset | Bytes | SHA-256 | `general.file_type` | Observed tensor types |
|---|---:|---:|---|---:|---|
| `hal0-brain-sft-F16.gguf` | F16 reference | 2,166,552,096 | `ed9d28c4eac1d7c291bc80d9410c243a3d28e655921ccaf90f2b6619aa24d2c3` | 1 | 170 `F16`, 49 `F32` |
| `hal0-brain-sft-Q4_0_ROCMFP4_COHERENT.gguf` | `Q4_0_ROCMFP4_COHERENT` | 664,952,352 | `062219355646f09e184cfb30cbfdfc429d70275f3be4d996d32644ec2b20db44` | 102 | 169 `Q4_0_ROCMFP4`, 1 `Q6_K`, 49 `F32` |
| `hal0-brain-sft-Q8_0_ROCMFPX_AGENT.gguf` | `Q8_0_ROCMFPX_AGENT` | 1,144,682,016 | `eeb38e45877d26a5923d2ec22e1c887a0b12f0c40f9df72015bd73f11d1263e4` | 115 | 58 `Q8_0_ROCMFPX`, 112 protected `Q8_0`, 49 `F32` |
| `chat-long-context.hal0profile.json` | portable hal0 profile | — | profile checksum `sha256:241af4cd2636ac1da32a8a7ca0d856724445242cfcde88a208b702b155bdee47` | — | `hal0.profile` schema 1 |
The Agent presets deliberately retain higher-precision tensors where structured behavior is most sensitive. The filenames are descriptive, but the format claims above come from ROCmFPX-aware GGUF inspection—not filename inference.
## Provenance
- Base model: [`Hal0ai/hal0-brain-sft`](https://huggingface.co/Hal0ai/hal0-brain-sft)
- Verified F16 GGUF source: [`Hal0ai/hal0-brain-sft-GGUF`](https://huggingface.co/Hal0ai/hal0-brain-sft-GGUF) at revision `6b190df6e816cc806f7fa7ae3de7248f5551e00b`
- F16 source SHA-256: `ed9d28c4eac1d7c291bc80d9410c243a3d28e655921ccaf90f2b6619aa24d2c3`
- Quantizer: [`charlie12345/ROCmFPX`](https://github.com/charlie12345/ROCmFPX) at commit `61f2f2d7bc4955e9bca821095ef69125837133b5`
- Architecture: Llama-compatible GGUF, approximately 1.08B parameters
- License: Apache-2.0
Both quantized files were produced independently from F16. Neither was requantized from another low-bit artifact.
## Runtime compatibility
| Artifact | Stock llama.cpp | ROCmFPX CPU reference | ROCmFPX HIP/ROCm | ROCmFPX Vulkan |
|---|---:|---:|---:|---:|
| F16 | ✅ | ✅ | ✅ | ✅ |
| Q4 ROCmFP4 Coherent | ❌ | ✅ | ✅ | ✅ |
| Q8 ROCmFPX Agent | ❌ | ✅ | ✅ | ✅ |
The Q4 and Q8 files contain custom GGML tensor types and require a **ROCmFPX-capable runner**. Current stock llama.cpp rejects the Q4 tensor type ID `100` and Q8 tensor type ID `103` as invalid/unknown. LM Studio, Ollama, or another stock llama.cpp package must not be assumed compatible.
hal0 pins the unified runner by immutable digest:
```text
ghcr.io/hal0ai/hal0-rocmfpx@sha256:fd6b02a720e633e402e929e19eedefff52aeec18e5de8f43e525689e523985f3
```
That runner contains the MiniCPM5 pre-tokenizer mapping required by this model and supports both ROCm/HIP and Vulkan ROCmFPX paths.
## Download
Install the Hugging Face CLI and authenticate only if your environment requires it:
```bash
pip install -U huggingface_hub
```
F16:
```bash
hf download Hal0ai/hal0-brain-sft-ROCmFPX-GGUF \
hal0-brain-sft-F16.gguf --local-dir .
```
ROCmFP4 Coherent Agent:
```bash
hf download Hal0ai/hal0-brain-sft-ROCmFPX-GGUF \
hal0-brain-sft-Q4_0_ROCMFP4_COHERENT.gguf --local-dir .
```
ROCmFP8 Agent:
```bash
hf download Hal0ai/hal0-brain-sft-ROCmFPX-GGUF \
hal0-brain-sft-Q8_0_ROCMFPX_AGENT.gguf --local-dir .
```
Portable hal0 long-context profile:
```bash
hf download Hal0ai/hal0-brain-sft-ROCmFPX-GGUF \
chat-long-context.hal0profile.json --local-dir .
```
## Run with ROCmFPX
ROCm/HIP:
```bash
llama-cli \
-m hal0-brain-sft-Q8_0_ROCMFPX_AGENT.gguf \
-dev ROCm0 -ngl 999 -fa on -c 8192 -b 512 -ub 512 --jinja
```
Vulkan:
```bash
llama-cli \
-m hal0-brain-sft-Q4_0_ROCMFP4_COHERENT.gguf \
-dev Vulkan0 -ngl 999 -fa on -c 8192 -b 512 -ub 512 --jinja
```
OpenAI-compatible server:
```bash
llama-server \
-m hal0-brain-sft-Q8_0_ROCMFPX_AGENT.gguf \
--host 0.0.0.0 --port 8080 \
-dev Vulkan0 -ngl 999 -fa on -c 8192 -b 512 -ub 512 --jinja
```
Choose `ROCm0` or `Vulkan0` according to the devices reported by the ROCmFPX runner. Long context and large batches consume substantial memory; tune them for the host.
## Tool-calling contract
hal0's catalog declares the `hal0-function-xml` prompt contract. A complete tool call has this shape:
```xml
<function name="memory_add">
<param name="text">Remember that the brain slot uses the ROCmFPX runner.</param>
</function>
```
The hal0 integration validates the tool schema, allows at most one complete tool call per turn, and stops after `</function>`.
## Portable hal0 profile
`chat-long-context.hal0profile.json` is a checksummed, portable `hal0.profile` schema-1 envelope. It includes:
```text
-fa on -ctk q8_0 -ctv q8_0 -b 2048 -ub 512 --parallel 1
--no-mmap --no-context-shift --poll 100 --poll-batch 1 --metrics --no-webui
```
These are performance-oriented defaults, not a hardware guarantee. Reduce context/batch settings or use another profile when the host cannot sustain them.
### Dashboard import
Open **Profiles**, choose **Import**, select `chat-long-context.hal0profile.json`, review the dry-run result, and commit the import. If `chat-long-context` already exists, choose another name rather than overwriting it implicitly.
### REST API dry-run and import
Dry-run validates the envelope and checksum without changing the profile catalog:
```bash
PROFILE=chat-long-context.hal0profile.json
jq -n --slurpfile envelope "$PROFILE" \
'{envelope:$envelope[0],name:"chat-long-context",dry_run:true}' |
curl --fail-with-body -sS http://127.0.0.1:8080/api/profiles/import \
-H 'content-type: application/json' --data-binary @-
```
Commit only after the dry-run reports `valid: true`, `checksum_ok: true`, and no unwanted collision:
```bash
PROFILE=chat-long-context.hal0profile.json
jq -n --slurpfile envelope "$PROFILE" \
'{envelope:$envelope[0],name:"chat-long-context",dry_run:false}' |
curl --fail-with-body -sS http://127.0.0.1:8080/api/profiles/import \
-H 'content-type: application/json' --data-binary @-
```
## Validation record
- ROCmFPX-aware inspection confirmed every file type and tensor count in the table.
- ROCmFPX CPU reference execution loaded and benchmarked both custom artifacts.
- The catalog runner image includes the required MiniCPM5 tokenizer mapping and ROCmFPX ROCm/Vulkan kernels.
- Stock llama.cpp `e8e6c7af2456fd50bb62f7a2bbd642e6fb14ae77` rejected Q4 type `100` and Q8 type `103` before tensor loading.
## Related
- [hal0](https://github.com/Hal0ai/hal0)
- [ROCmFPX](https://github.com/charlie12345/ROCmFPX)
- [Hal0ai model collection](https://huggingface.co/collections/Hal0ai/hal0-brain-6a5e1859dbae8e442c659141)
|