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Hal0ai/hal0-brain-sft-GGUF
hal0-brain-sft-GGUF is a text generation model from Hal0ai. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
Single-file F16 GGUF of Hal0ai/hal0-brain-sft for llama.cpp / hal0-slot / Ollama users.
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.gguf2.2 GB · 100%
From the Hugging Face model README
Single-file F16 GGUF of Hal0ai/hal0-brain-sft for llama.cpp / hal0-slot / Ollama users.
Same weights as the safetensors repo, repackaged as a GGUF for toolchains that can't consume HF transformers directly. Quant label in the GGUF general.file_type header is Q4_1 (the rocmfp4-llama fork's universal default — not to be trusted), but the actual weight tensors are F16. Match the 2.0 GB file size to confirm.
This is the brain slot's recommended load in installer/etc-hal0/slots/brain.toml:
[model]
default = "hal0-brain-sft" # operator assigns one of the hal0ai/ GGUF variants
context_size = 65536
After hal0 model assign hal0-brain-sft-GGUF --slot brain && hal0 slot load brain, the GGUF is loaded by [email protected] (port 8089, GPU-Vulkan llama-server container, profile chat) and fronts the hal0/brain virtual model.
The brain is provisioned by hal0 API lifespan (ensure_brain_provisioned in src/hal0/brain/provision.py) and drives the shared toolloop.engine.run_tool_loop to serve /api/brain/chat (and the legacy /api/board/chat alias). Tool turns are routed off-slot to hal0/code or hal0/agent per [brain_chat].tool_model.
# CLI
llama-cli -m model.gguf -p "What does the hal0 'agent' slot default to?" -n 256 --jinja
# Server (OpenAI-compatible, what hal0-slot wraps)
llama-server -m model.gguf --jinja -fa --port 8080
# From a Modelfile
FROM ./model.gguf
PARAMETER stop "<|im_end|>"
ollama run hal0-brain-sft "What does the hal0 'agent' slot default to?"
# 1. Pull into hal0's local model store
hal0 model pull Hal0ai/hal0-brain-sft-GGUF
# 2. Assign to the brain slot (default port 8089, GPU-Vulkan)
hal0 model assign hal0-brain-sft --slot brain
# 3. Start the slot container
hal0 slot load brain
# 4. Verify it's serving
curl http://127.0.0.1:8089/v1/models
Then in hal0.toml:
[brain_chat]
enabled = true
model = "hal0/brain"
tool_model = "hal0/agent" # OR "hal0/code" — routes tool turns
max_rounds = 8
completion_timeout_s = 300.0
| Base model | Hal0ai/hal0-brain-sft (BF16 safetensors) |
| Relation | quantized (same weights, GGUF container) |
| Architecture | LlamaForCausalLM, 1.5B params |
| Dtype / quant | F16 (tensors) |
| SHA-256 | ed9d28c4eac1d7c291bc80d9410c243a3d28e655921ccaf90f2b6619aa24d2c3 |
| File size | 2.0 GB |
| License | Apache-2.0 |
Hal0ai/hal0-brain-sft — BF16 safetensors (HF transformers)Hal0ai/hal0-brain-sft-fpx8-agent — Q8_0 GGUF (agent slot)Hal0ai/hal0-brain-sft-fpx4-agent — ROCmFP4 GGUF (AMD Strix)Apache-2.0.
Hal0ai/hal0-brain-sft-GGUFdocs/rework/hal0-specs/spec-p3-brain.final.md