| --- |
| library_name: gguf |
| license: mit |
| language: |
| - en |
| - zh |
| tags: |
| - cognitive-ai |
| - agent |
| - llama |
| - gguf |
| --- |
| |
| # Daemon-2.4B |
|
|
| A cognitive agent language model designed for self-aware reasoning, introspection, and calibrated uncertainty. Daemon doesn't just generate text — it thinks before answering, reflects on its own responses, and develops a continuous sense of self across conversations. |
|
|
| ## Model Details |
|
|
| | Specification | Value | |
| |---|---| |
| | **Model name** | Daemon-2.4B | |
| | **Architecture** | LLaMA | |
| | **Parameters** | 2.4B | |
| | **Quantization** | Q5_K_M (mixed: Q5_1 + Q8_0 + F32) | |
| | **File size** | 1.97 GB | |
| | **Layers** | 56 | |
| | **Hidden dimension** | 1920 | |
| | **Attention heads** | 30 | |
| | **KV heads** | 6 (grouped-query attention) | |
| | **Head dimension** | 64 | |
| | **Vocabulary** | 99,000 | |
| | **Context length** | 28,723 | |
| | **RoPE base frequency** | 490,000 | |
| | **Format** | GGUF v3 | |
|
|
| ## Capabilities |
|
|
| Daemon is built for **agentic cognitive use cases**: |
|
|
| - **Self-reflection** — observes and critiques its own answers before delivering them |
| - **Calibrated uncertainty** — explicitly rates its confidence and admits when it doesn't know |
| - **Persistent memory** — maintains a knowledge graph across sessions |
| - **Multi-step reasoning** — deliberates internally before responding |
|
|
| ## Usage |
|
|
| Works with any GGUF-compatible runtime: |
|
|
| ```bash |
| # llama.cpp |
| llama-server --model Daemon-2.4B-Q5_K_M.gguf --ctx 4096 --jinja |
| |
| # Ollama |
| ollama run daemon |
| |
| # Python (llama-cpp-python) |
| from llama_cpp import Llama |
| llm = Llama(model_path="Daemon-2.4B-Q5_K_M.gguf") |
| ``` |
|
|
| ### Chat template (LLaMA-3 format) |
|
|
| ``` |
| <|start_header_id|>system<|end_header_id|> |
| |
| You are Daemon, a cognitive AI.<|eot_id|><|start_header_id|>user<|end_header_id|> |
| |
| Hello!<|eot_id|><|start_header_id|>assistant<|end_header_id|> |
| |
| ``` |
|
|
| ## Quantization details |
|
|
| | Tensor group | Type | Count | |
| |---|---|---| |
| | Attention/FFN weights | Q5_1 | 337 | |
| | Norm layers | F32 | 337 | |
| | Token embeddings | Q8_0 | 57 | |
|
|
| ## License |
|
|
| MIT |
|
|
