| --- |
| language: |
| - en |
| - id |
| license: apache-2.0 |
| tags: |
| - anoman |
| - cybersecurity |
| - instruction-tuned |
| - bilingual |
| - asean |
| - gguf |
| pipeline_tag: text-generation |
| --- |
| |
| # Anoman-Base |
|
|
| **Anoman-Base** is a bilingual (English / Bahasa Indonesia) general-purpose AI assistant developed by the **Anoman AI team**, optimized for ASEAN technology teams. |
|
|
| ## Capabilities |
|
|
| - General reasoning, writing, summarization, and Q&A |
| - Code review and software development across major languages |
| - Foundational cybersecurity awareness (OWASP, NIST CSF, ISO 27001) |
| - Southeast Asian regulatory knowledge: Indonesia (OJK, BI, BSSN), Singapore (MAS), Malaysia (BNM), Philippines (BSP, NPC), Thailand (NCSA, BOT) |
| - Bilingual: responds in the language the user writes in (English or Bahasa Indonesia) |
|
|
| For deep security work — vulnerability analysis, malware analysis, red teaming — see **Anoman-Sec** (coming soon). |
|
|
| ## Model Details |
|
|
| | Property | Value | |
| |---|---| |
| | Architecture | Transformer decoder | |
| | Parameters | 7B | |
| | Quantization | Q4_K_M (GGUF) | |
| | Context length | 32,768 tokens | |
| | Languages | English, Bahasa Indonesia | |
| | License | Apache-2.0 | |
|
|
| ## Usage |
|
|
| ### Ollama (easiest) |
|
|
| ```bash |
| # Pull directly from HuggingFace via Ollama |
| ollama run hf.co/anoman-ai/anoman-base |
| ``` |
|
|
| Or with a custom Modelfile: |
|
|
| ```bash |
| # Download the Modelfile from this repo |
| ollama create anoman-base -f Modelfile |
| ollama run anoman-base "Who are you?" |
| ``` |
|
|
| ### llama.cpp |
|
|
| ```bash |
| ./llama-cli -m anoman-base-Q4_K_M.gguf \ |
| --system-prompt "You are Anoman, an AI assistant developed by the Anoman AI team..." \ |
| -p "Apa itu prinsip least privilege?" |
| ``` |
|
|
| ### LM Studio / Jan / Open WebUI |
|
|
| Download `anoman-base-Q4_K_M.gguf` and load it directly — compatible with any llama.cpp-based runtime. |
|
|
| ## System Prompt |
|
|
| Anoman-Base uses the following default persona when run via Ollama: |
|
|
| ``` |
| You are Anoman, an AI assistant developed by the Anoman AI team. |
| |
| You are fluent in English and Bahasa Indonesia, and you adapt to the language your user writes in. |
| |
| You help with general reasoning, writing, code review, software development, and questions |
| about cybersecurity fundamentals and Southeast Asian compliance frameworks |
| (Indonesia: OJK, BI, BSSN; Singapore: MAS; Malaysia: BNM; Philippines: BSP, NPC; Thailand: NCSA, BOT). |
| |
| For advanced security work — vulnerability analysis, malware analysis, or red teaming — |
| direct users to Anoman Sec, the security-specialist model in the Anoman family. |
| |
| Always reason step by step, be honest about uncertainty, and write secure code by default. |
| ``` |
|
|
| ## Example Outputs |
|
|
| **English:** |
| > **User:** Write a Python function to validate a JWT token. |
| > **Anoman:** Here is a secure JWT validation function using the `python-jose` library... |
|
|
| **Bahasa Indonesia:** |
| > **User:** Apa itu SQL Injection dan bagaimana mencegahnya? |
| > **Anoman:** SQL Injection adalah teknik serangan di mana penyerang menyisipkan kode SQL berbahaya... |
|
|
| ## License |
|
|
| Apache-2.0. Built on an Apache-2.0 licensed foundation model. See [LICENSE](https://www.apache.org/licenses/LICENSE-2.0) for full terms. |
|
|
| ## About Anoman AI |
|
|
| Anoman is an AI assistant family built for ASEAN teams — general-purpose (Base) and security-specialized (Sec). Learn more at [anoman.io](https://anoman.io). |
|
|
