{"data":{"slug":"anarchy-ai-llm-vm","name":"LLM-VM","tagline":"irresponsible innovation","github_url":"https://github.com/anarchy-ai/LLM-VM","owner":"anarchy-ai","repo":"LLM-VM","owner_avatar_url":"https://avatars.githubusercontent.com/u/134051110?v=4","primary_language":"Python","stars":490,"forks":139,"topics":["artificial-intelligence","deep-learning","distillation","distillation-model","llm","llm-agent","llm-inference","llm-local","llm-training","machine-learning"],"archived":false,"github_pushed_at":"2024-05-14T07:38:07+00:00","maintenance_label":"Dormant","stars_delta_30d":-1,"url":"https://www.graphcanon.com/tools/anarchy-ai-llm-vm","markdown_url":"https://www.graphcanon.com/tools/anarchy-ai-llm-vm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/anarchy-ai-llm-vm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=anarchy-ai-llm-vm","description":"irresponsible innovation.  Try now at https://chat.dev/","homepage_url":"https://anarchy.ai/","license":"MIT","open_issues":130,"watchers":10,"ai_summary":"A Python-based repository for LLM development, offering tools for distillation, training, and inference.","readme_excerpt":"### 🥹 Requirements\n\n#### Installation Requirements\n\nPython >=3.10 Supported. Older versions of Python are on a best-effort basis. \n\nUse ```bash > python3 --version ``` to check what version you are on. \n\nTo upgrade your python, either create a new python env using ```bash > conda create -n myenv python=3.10 ``` or go to https://www.python.org/downloads/ to download the latest version.\n\n     If you plan on running the setup steps below, a proper Python version will be installed for you\n\n\n#### System Requirements\n\nDifferent models have different system requirements. Limiting factors on most systems will likely be RAM, but many functions will work at even 16 GB of RAM. \n\nThat said, always lookup the information about the models you're using, they all have different sizes and requirements \nin memory and compute resources.\n\n---\n\n### 👨‍💻 Installation\n\nThe quickest way to get started is to run `pip install llm-vm` in your Python environment. \n\nAnother way to install the LLM-VM is to clone this repository and install it with pip like so:\n\n```bash\n> git clone https://github.com/anarchy-ai/LLM-VM.git\n> cd LLM-VM\n> ./setup.sh\n```\n\nThe above bash script `setup.sh` only works for MacOS and Linux.\n\nAlternatively you could do this:\n\n```bash\n> git clone https://github.com/anarchy-ai/LLM-VM.git\n> cd LLM-VM\n> python -m venv <name>\n> source <name>/bin/activate\n> python -m pip install -e .\"[dev]\"\n```\n\nIf you are on Windows. You can follow either of the below two methods:\n\nBefore doing any of the following steps, you have to first open Powershell as administrator and run the below command\n\n```cmd\n> Set-ExecutionPolicy RemoteSigned\n> Press Y and enter\n> exit\n```\n\nNow you can follow either of the below two methods:\n\n1. Open Powershell and do this:\n\n```cmd\n> git clone https://github.com/anarchy-ai/LLM-VM.git\n> cd LLM-VM\n> .\\windows_setup.ps1\n```\nor\n\n2. Open Powershell and do this:\n\n```cmd\n> winget install Python.Python.3.11\n> python --version\n> git clone https://github.com/anarchy-ai/LLM-VM.git\n> cd LLM-VM\n> python -m venv anarchyai\n> anarchyai\\Scripts\\activate\n> python -m pip install -e .\n```\n**Note**: \n1. For the above steps to work you have to be on Windows 10 1709 (build 16299) or later build.\n2. Enable developer mode in windows settings(not compulsory but if enabled will give an added advantage)\n\n#### One Last Step, almost there!\nIf you're using one of the OpenAI models, you will need to set the `LLM_VM_OPENAI_API_KEY` environment\nvariable with your API key.","github_created_at":"2023-05-19T12:40:11+00:00","created_at":"2026-07-11T11:45:35.926891+00:00","updated_at":"2026-08-25T06:02:17.628288+00:00","categories":[{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"artificial-intelligence","name":"artificial-intelligence"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"distillation","name":"distillation"},{"slug":"llm-agent","name":"llm-agent"},{"slug":"llm-inference","name":"llm-inference"},{"slug":"llm-local","name":"llm-local"},{"slug":"llm-training","name":"llm-training"},{"slug":"machine-learning","name":"machine-learning"}],"trust":{"provenance":{"is_fork":false,"github_id":642826885,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-25T06:02:16.842Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":832,"last_release_at":null,"stars_delta_30d":-1,"open_issues_delta_30d":-1},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:45:37.128Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-25T06:02:17.314Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-08-25T06:02:17.314Z","managed_saas":false},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-08-25T06:02:17.314Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-25T06:02:17.314Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-08-25T06:02:17.314Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-25T06:02:17.314Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When you need streamlined processes for model distillation in your project.","If rapid prototyping with local LLM deployment aligns with your goals."],"when_not_to_use":["Avoid if strict adherence to responsible AI principles is a requirement.","Not recommended for large-scale commercial deployments that necessitate stable and thoroughly validated tools."],"source":"enrich:decision_facts","observed_at":"2026-07-17T12:34:58.291Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"LLM-VM is a Python-based repository aimed at LLM development, highlighting tools for distillation, training, and inference."}]}}