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MODEL Listed

altar-1

For developers working in the security and automated reasoning space, altar-1 represents a specialized approach to text generation. While many general-purpose LLMs are tuned heavily for conversational politeness, altar-1 is positioned as a tool for more technical, structured text generation tasks. For those integrating AI into DevSecOps pipelines or automated documentation workflows, this model offers a different behavioral profile than the standard consumer-grade assistants. It is designed to be integrated via the Hugging Face ecosystem, making it straightforward to deploy within existing Python-based inference stacks. While parameter counts are not explicitly disclosed, its utility lies in its niche application within the AikidoSec framework. If your use case involves generating technical content where standard safety guardrails might over-refuse legitimate technical queries, altar-1 provides a useful alternative for testing and development.

AikidoSectext generation
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01 / MODEL CARD

Model card

For developers working in the security and automated reasoning space, altar-1 represents a specialized approach to text generation. While many general-purpose LLMs are tuned heavily for conversational politeness, altar-1 is positioned as a tool for more technical, structured text generation tasks. For those integrating AI into DevSecOps pipelines or automated documentation workflows, this model offers a different behavioral profile than the standard consumer-grade assistants. It is designed to be integrated via the Hugging Face ecosystem, making it straightforward to deploy within existing Python-based inference stacks. While parameter counts are not explicitly disclosed, its utility lies in its niche application within the AikidoSec framework. If your use case involves generating technical content where standard safety guardrails might over-refuse legitimate technical queries, altar-1 provides a useful alternative for testing and development.

Model typetext generation
ProviderAikidoSec
Licenseother
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/AikidoSec/altar-1
View model source
Version informationUse the source repository for the latest version
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03 / DOWNLOAD

Download this model

We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.

This entry points to Hugging Face. The commands use the matching ModelScope repository format; confirm that the repository exists on ModelScope before running them. Model repository: AikidoSec/altar-1
Install ModelScope

Install the CLI and SDK dependency before downloading.

pip install modelscope
Download the full model repository

Download the complete weights, configuration and model card.

modelscope download --model AikidoSec/altar-1
Download one file to a local directory

README.md is used as an example; replace it with another repository file when needed.

modelscope download --model AikidoSec/altar-1 README.md --local_dir ./dir
Download with the SDK

Useful in Python projects and automation scripts.

from modelscope import snapshot_download
model_dir = snapshot_download('AikidoSec/altar-1')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/AikidoSec/altar-1.git
Clone without downloading LFS blobs

Fetch the repository structure first, then pull large files when needed.

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/AikidoSec/altar-1.git
04 / WORKFLOW

How to use

  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

Discussions

Use this space to keep checking source information, usage experience and maintenance status.

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