Dockerize Ollama models #23
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| name: 'Dockerize Ollama models' | |
| on: | |
| workflow_dispatch: | |
| inputs: | |
| ollama_version: | |
| description: 'Ollama version' | |
| required: true | |
| default: 'latest' | |
| jobs: | |
| build: | |
| runs-on: ubuntu-latest | |
| strategy: | |
| matrix: | |
| models: [ | |
| model: { | |
| name: 'all-minilm', | |
| tag: '22m', | |
| description: 'Embedding models on very large sentence level datasets' | |
| }, | |
| model: { | |
| name: 'bge-m3', | |
| tag: '567m', | |
| description: 'BGE-M3 is a new model from BAAI distinguished for its versatility in Multi-Functionality, Multi-Linguality, and Multi-Granularity' | |
| }, | |
| model: { | |
| name: 'codegemma', | |
| tag: '7b', | |
| description: 'CodeGemma is a collection of powerful, lightweight models that can perform a variety of coding tasks like fill-in-the-middle code completion, code generation, natural language understanding, mathematical reasoning, and instruction following' | |
| }, | |
| model: { | |
| name: 'deepseek-coder', | |
| tag: '1.3b', | |
| description: 'DeepSeek Coder is a capable coding model trained on two trillion code and natural language tokens' | |
| }, | |
| model: { | |
| name: 'gemma2', | |
| tag: '2b', | |
| description: 'Google Gemma 2 is a high-performing and efficient model available in three sizes: 2B, 9B, and 27B' | |
| }, | |
| model: { | |
| name: 'llama3.1', | |
| tag: '8b', | |
| description: 'Llama 3.1 is a new state-of-the-art model from Meta available in 8B, 70B and 405B parameter sizes' | |
| }, | |
| model: { | |
| name: 'llama3.2', | |
| tag: '1b', | |
| description: 'Llama 3.2 of Meta goes small with 1B and 3B models.' | |
| }, | |
| model: { | |
| name: 'llama3.2', | |
| tag: '3b', | |
| description: 'Llama 3.2 of Meta goes small with 1B and 3B models.' | |
| }, | |
| model: { | |
| name: 'llava', | |
| tag: '7b', | |
| description: 'LLaVA is a novel end-to-end trained large multimodal model that combines a vision encoder and Vicuna for general-purpose visual and language understanding. Updated to version 1.6' | |
| }, | |
| model: { | |
| name: 'llava-phi3', | |
| tag: '3.8b', | |
| description: 'A new small LLaVA model fine-tuned from Phi 3 Mini' | |
| }, | |
| model: { | |
| name: 'mistral', | |
| tag: '7b', | |
| description: 'The 7B model released by Mistral AI, updated to version 0.3' | |
| }, | |
| model: { | |
| name: 'moondream', | |
| tag: '1.8b', | |
| description: 'moondream2 is a small vision language model designed to run efficiently on edge devices' | |
| }, | |
| model: { | |
| name: 'mxbai-embed-large', | |
| tag: '335m', | |
| description: 'State-of-the-art large embedding model from mixedbread.ai' | |
| }, | |
| model: { | |
| name: 'nomic-embed-text', | |
| tag: 'v1.5', | |
| description: 'A high-performing open embedding model with a large token context window' | |
| }, | |
| model: { | |
| name: 'phi3', | |
| tag: '3.8b', | |
| description: 'Phi-3 is a family of lightweight 3B (Mini) and 14B (Medium) state-of-the-art open models by Microsoft' | |
| }, | |
| model: { | |
| name: 'phi3.5', | |
| tag: '3.8b', | |
| description: 'A lightweight AI model with 3.8 billion parameters with performance overtaking similarly and larger sized models' | |
| }, | |
| model: { | |
| name: 'qwen2', | |
| tag: '0.5b', | |
| description: 'Qwen2 is a new series of large language models from Alibaba group' | |
| }, | |
| model: { | |
| name: 'qwen2.5', | |
| tag: '0.5b-instruct', | |
| description: 'Qwen2.5 models are pretrained on Alibaba latest large-scale dataset, encompassing up to 18 trillion tokens. The model supports up to 128K tokens and has multilingual support' | |
| }, | |
| model: { | |
| name: 'qwen2.5-coder', | |
| tag: '1.5b', | |
| description: 'The latest series of Code-Specific Qwen models, with significant improvements in code generation, code reasoning, and code fixing.' | |
| }, | |
| model: { | |
| name: 'snowflake-arctic-embed', | |
| tag: '335m', | |
| description: 'A suite of text embedding models by Snowflake, optimized for performance' | |
| }, | |
| model: { | |
| name: 'starcoder2', | |
| tag: '3b', | |
| description: 'StarCoder2 is the next generation of transparently trained open code LLMs that comes in three sizes: 3B, 7B and 15B parameters' | |
| }, | |
| model: { | |
| name: 'reader-lm', | |
| tag: '1.5b', | |
| description: 'A series of models that convert HTML content to Markdown content, which is useful for content conversion tasks' | |
| }, | |
| model: { | |
| name: 'bespoke-minicheck', | |
| tag: '7b', | |
| description: 'A SOTA fact-checking model developed by Bespoke Labs' | |
| } | |
| ] | |
| steps: | |
| - name: Free Disk Space | |
| uses: jlumbroso/free-disk-space@54081f138730dfa15788a46383842cd2f914a1be # v1.3.1 | |
| with: | |
| tool-cache: true | |
| - name: Checkout repository | |
| uses: actions/checkout@v4 | |
| - name: Build and Deploy Docker Image | |
| uses: ./ | |
| with: | |
| docker_username: ${{ secrets.DOCKER_USERNAME }} | |
| docker_password: ${{ secrets.DOCKER_PASSWORD }} | |
| docker_repository: ${{ matrix.models.model.name }} | |
| docker_tag: ${{ github.event.inputs.ollama_version }}-${{ matrix.models.model.tag }} | |
| model_name: ${{ matrix.models.model.name }} | |
| model_tag: ${{ matrix.models.model.tag }} | |
| ollama_version: ${{ github.event.inputs.ollama_version }} | |
| short_description: ${{ matrix.models.model.description }} |