{"id":15165989,"url":"https://github.com/sammcj/gollama","last_synced_at":"2025-05-14T23:04:22.960Z","repository":{"id":242115075,"uuid":"808123482","full_name":"sammcj/gollama","owner":"sammcj","description":"Go manage your Ollama models","archived":false,"fork":false,"pushed_at":"2025-05-03T04:32:40.000Z","size":2250,"stargazers_count":1047,"open_issues_count":4,"forks_count":56,"subscribers_count":9,"default_branch":"main","last_synced_at":"2025-05-03T05:26:11.846Z","etag":null,"topics":["ai","ggml","gguf","linux","llm","macos","models","ollama","tui"],"latest_commit_sha":null,"homepage":"https://smcleod.net","language":"Go","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sammcj.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":".github/FUNDING.yml","license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":"CODEOWNERS","security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null},"funding":{"github":"sammcj","buy_me_a_coffee":"sam.mcleod"}},"created_at":"2024-05-30T12:35:37.000Z","updated_at":"2025-05-03T04:31:24.000Z","dependencies_parsed_at":"2024-06-27T07:28:14.914Z","dependency_job_id":"ee51e9aa-2258-4509-9867-e0a6b570a69c","html_url":"https://github.com/sammcj/gollama","commit_stats":{"total_commits":143,"total_committers":8,"mean_commits":17.875,"dds":0.1678321678321678,"last_synced_commit":"bda53dc7d3ac1446baa325b03d79b68a77b0ec04"},"previous_names":["sammcj/gollama"],"tags_count":217,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sammcj%2Fgollama","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sammcj%2Fgollama/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sammcj%2Fgollama/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sammcj%2Fgollama/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sammcj","download_url":"https://codeload.github.com/sammcj/gollama/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254243358,"owners_count":22038046,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","ggml","gguf","linux","llm","macos","models","ollama","tui"],"created_at":"2024-09-27T04:21:53.684Z","updated_at":"2025-05-14T23:04:22.939Z","avatar_url":"https://github.com/sammcj.png","language":"Go","funding_links":["https://github.com/sponsors/sammcj","https://buymeacoffee.com/sam.mcleod"],"categories":["Go","macos","A01_文本生成_文本对话","ai"],"sub_categories":["大语言对话模型及数据"],"readme":"# Gollama\n\n![](gollama-logo.png)\n\nGollama is a macOS / Linux tool for managing Ollama models.\n\nIt provides a TUI (Text User Interface) for listing, inspecting, deleting, copying, and pushing Ollama models as well as optionally linking them to LM Studio*.\n\nThe application allows users to interactively select models, sort, filter, edit, run, unload and perform actions on them using hotkeys.\n\n![](screenshots/gollama-v1.0.0.jpg)\n\n## Table of Contents\n\n- [Gollama](#gollama)\n  - [Table of Contents](#table-of-contents)\n  - [Features](#features)\n  - [Installation](#installation)\n    - [go install (recommended)](#go-install-recommended)\n    - [curl](#curl)\n    - [Manually](#manually)\n    - [if \"command not found: gollama\"](#if-command-not-found-gollama)\n  - [Usage](#usage)\n    - [Key Bindings](#key-bindings)\n      - [Top](#top)\n      - [Inspect](#inspect)\n      - [Link](#link)\n      - [Spit (Copy to Remote)](#spit-copy-to-remote)\n      - [Command-line Options](#command-line-options)\n  - [Configuration](#configuration)\n  - [Installation and build from source](#installation-and-build-from-source)\n    - [Themes](#themes)\n  - [Logging](#logging)\n  - [Contributing](#contributing)\n  - [Acknowledgements](#acknowledgements)\n  - [License](#license)\n\n## Features\n\nThe project started off as a rewrite of my [llamalink](https://smcleod.net/2024/03/llamalink-ollama-to-lm-studio-llm-model-linker/) project, but I decided to expand it to include more features and make it more user-friendly.\n\nIt's in active development, so there are some bugs and missing features, however I'm finding it useful for managing my models every day, especially for cleaning up old models.\n\n- List available models\n- Display metadata such as size, quantisation level, model family, and modified date\n- Edit / update a model's Modelfile\n- Sort models by name, size, modification date, quantisation level, family etc\n- Select and delete models\n- Run and unload models\n- Inspect model for additional details\n- Calculate approximate vRAM usage for a model\n- Link models to LM Studio\n- Copy / rename models\n- Push models to a registry\n- Copy models to remote hosts (spit)\n- Show running models\n- Has some cool bugs\n\nSee also - [ingest](https://github.com/sammcj/ingest) for passing directories/repos of code to markdown formatted for LLMs.\n\nGollama Intro (\"Podcast\" Episode):\n\n\u003caudio src=\"https://github.com/sammcj/smcleod_files/raw/refs/heads/master/audio/podcast-ep-sw/Podcast%20Episode%20-%20Gollama.mp3\" controls preload\u003e\u003c/audio\u003e\n\n## Installation\n\n### go install (recommended)\n\n```shell\ngo install github.com/sammcj/gollama@HEAD\n```\n\n### curl\n\nI don't recommend this method as it's not as easy to update, but you can use the following command:\n\n```shell\ncurl -sL https://raw.githubusercontent.com/sammcj/gollama/refs/heads/main/scripts/install.sh | bash\n```\n\n### Manually\n\nDownload the most recent release from the [releases page](https://github.com/sammcj/gollama/releases) and extract the binary to a directory in your PATH.\n\ne.g. `zip -d gollama*.zip -d gollama \u0026\u0026 mv gollama /usr/local/bin`\n\n### if \"command not found: gollama\"\n\nIf you see this error, add environment variables to `.zshrc` or `.bashrc`.\n\n```shell\necho 'export PATH=$PATH:$HOME/go/bin' \u003e\u003e ~/.zshrc\nsource ~/.zshrc\n```\n\n## Usage\n\nTo run the `gollama` application, use the following command:\n\n```sh\ngollama\n```\n\n_Tip_: I like to alias gollama to `g` for quick access:\n\n```shell\necho \"alias g=gollama\" \u003e\u003e ~/.zshrc\n```\n\n### Key Bindings\n\n- `Space`: Select\n- `Enter`: Run model (Ollama run)\n- `i`: Inspect model\n- `t`: Top (show running models)\n- `D`: Delete model\n- `e`: Edit model\n- `c`: Copy model\n- `U`: Unload all models\n- `p`: Pull an existing model\n- `ctrl+k`: Pull model \u0026 preserve user configuration\n- `ctrl+p`: Pull (get) new model\n- `P`: Push model\n- `n`: Sort by name\n- `s`: Sort by size\n- `m`: Sort by modified\n- `k`: Sort by quantisation\n- `f`: Sort by family\n- `B`: Sort by parameter size\n- `l`: Link model to LM Studio\n- `L`: Link all models to LM Studio\n- `r`: Rename model _**(Work in progress)**_\n- `q`: Quit\n\n#### Top\n\nTop (`t`)\n\n![](screenshots/gollama-top.jpg)\n\n#### Inspect\n\nInspect (`i`)\n\n![](screenshots/gollama-inspect.png)\n\n#### Link\n\nLink (`l`), Link All (`L`) and Link in the reverse direction: (`link-lmstudio`)\n\nWhen linking models to LM Studio, Gollama creates a Modelfile with the template from LM-Studio and a set of default parameters that you can adjust.\n\nNote: Linking requires admin privileges if you're running Windows.\n\n#### Spit (Copy to Remote)\n\nThe spit functionality allows you to copy Ollama models to remote hosts. This is useful for distributing models across multiple machines or creating backups.\n\nYou can use the command-line interface:\n\n```shell\n# Copy a specific model to a remote host\ngollama --spit my-model --remote http://remote-host:11434\n\n# Copy all models to a remote host\ngollama --spit-all --remote http://remote-host:11434\n```\n\nThis functionality uses the [spitter](https://github.com/sammcj/spitter) package to handle the model copying process.\n\n#### Command-line Options\n\n- `-l`: List all available Ollama models and exit\n- `-L`: Link all available Ollama models to LM Studio and exit\n- `-link-lmstudio`: Link all available LM Studio models to Ollama and exit\n- `--dry-run`: Show what would be linked without making any changes (use with -link-lmstudio or -L)\n- `-s \u003csearch term\u003e`: Search for models by name\n  - OR operator (`'term1|term2'`) returns models that match either term\n  - AND operator (`'term1\u0026term2'`) returns models that match both terms\n- `-e \u003cmodel\u003e`: Edit the Modelfile for a model\n- `-ollama-dir`: Custom Ollama models directory\n- `-lm-dir`: Custom LM Studio models directory\n- `-cleanup`: Remove all symlinked models and empty directories and exit\n- `-no-cleanup`: Don't cleanup broken symlinks\n- `-u`: Unload all running models\n- `-v`: Print the version and exit\n- `-h`, or `--host`: Specify the host for the Ollama API\n- `-H`: Shortcut for `-h http://localhost:11434` (connect to local Ollama API)\n- `--spit \u003cmodel\u003e`: Copy a model to a remote host\n- `--spit-all`: Copy all models to a remote host\n- `--remote \u003curl\u003e`: Remote host URL for spit operations (e.g., http://remote-host:11434)\n- `--vram`: Estimate vRAM usage for a model. Accepts:\n  - Ollama models (e.g. `llama3.1:8b-instruct-q6_K`, `qwen2:14b-q4_0`)\n  - HuggingFace models (e.g. `NousResearch/Hermes-2-Theta-Llama-3-8B`)\n  - `--fits`: Available memory in GB for context calculation (e.g. `6` for 6GB)\n  - `--vram-to-nth` or `--context`: Maximum context length to analyze (e.g. `32k` or `128k`)\n  - `--quant`: Override quantisation level (e.g. `Q4_0`, `Q5_K_M`)\n\n##### Simple model listing\n\nGollama can also be called with `-l` to list models without the TUI.\n\n```shell\ngollama -l\n```\n\nList (`gollama -l`):\n\n![](screenshots/cli-list.jpg)\n\n##### Edit\n\nGollama can be called with `-e` to edit the Modelfile for a model.\n\n```shell\ngollama -e my-model\n```\n\n##### Search\n\nGollama can be called with `-s` to search for models by name.\n\n```shell\ngollama -s my-model # returns models that contain 'my-model'\n\ngollama -s 'my-model|my-other-model' # returns models that contain either 'my-model' or 'my-other-model'\n\ngollama -s 'my-model\u0026instruct' # returns models that contain both 'my-model' and 'instruct'\n```\n\n##### vRAM Estimation\n\nGollama includes a comprehensive vRAM estimation feature:\n\n- Calculate vRAM usage for a pulled Ollama model (e.g. `my-model:mytag`), or huggingface model ID (e.g. `author/name`)\n- Determine maximum context length for a given vRAM constraint\n- Find the best quantisation setting for a given vRAM and context constraint\n- Shows estimates for different k/v cache quantisation options (fp16, q8_0, q4_0)\n- Automatic detection of available CUDA vRAM (**coming soon!**) or system RAM\n\n![](screenshots/vram.png)\n\nTo estimate (v)RAM usage:\n\n```shell\ngollama --vram llama3.1:8b-instruct-q6_K\n\n📊 VRAM Estimation for Model: llama3.1:8b-instruct-q6_K\n\n| QUANT   | CTX  | BPW | 2K  | 8K              | 16K             | 32K             | 49K             | 64K |\n| ------- | ---- | --- | --- | --------------- | --------------- | --------------- | --------------- |\n| IQ1_S   | 1.56 | 2.2 | 2.8 | 3.7(3.7,3.7)    | 5.5(5.5,5.5)    | 7.3(7.3,7.3)    | 9.1(9.1,9.1)    |\n| IQ2_XXS | 2.06 | 2.6 | 3.3 | 4.3(4.3,4.3)    | 6.1(6.1,6.1)    | 7.9(7.9,7.9)    | 9.8(9.8,9.8)    |\n| IQ2_XS  | 2.31 | 2.9 | 3.6 | 4.5(4.5,4.5)    | 6.4(6.4,6.4)    | 8.2(8.2,8.2)    | 10.1(10.1,10.1) |\n| IQ2_S   | 2.50 | 3.1 | 3.8 | 4.7(4.7,4.7)    | 6.6(6.6,6.6)    | 8.5(8.5,8.5)    | 10.4(10.4,10.4) |\n| IQ2_M   | 2.70 | 3.2 | 4.0 | 4.9(4.9,4.9)    | 6.8(6.8,6.8)    | 8.7(8.7,8.7)    | 10.6(10.6,10.6) |\n| IQ3_XXS | 3.06 | 3.6 | 4.3 | 5.3(5.3,5.3)    | 7.2(7.2,7.2)    | 9.2(9.2,9.2)    | 11.1(11.1,11.1) |\n| IQ3_XS  | 3.30 | 3.8 | 4.5 | 5.5(5.5,5.5)    | 7.5(7.5,7.5)    | 9.5(9.5,9.5)    | 11.4(11.4,11.4) |\n| Q2_K    | 3.35 | 3.9 | 4.6 | 5.6(5.6,5.6)    | 7.6(7.6,7.6)    | 9.5(9.5,9.5)    | 11.5(11.5,11.5) |\n| Q3_K_S  | 3.50 | 4.0 | 4.8 | 5.7(5.7,5.7)    | 7.7(7.7,7.7)    | 9.7(9.7,9.7)    | 11.7(11.7,11.7) |\n| IQ3_S   | 3.50 | 4.0 | 4.8 | 5.7(5.7,5.7)    | 7.7(7.7,7.7)    | 9.7(9.7,9.7)    | 11.7(11.7,11.7) |\n| IQ3_M   | 3.70 | 4.2 | 5.0 | 6.0(6.0,6.0)    | 8.0(8.0,8.0)    | 9.9(9.9,9.9)    | 12.0(12.0,12.0) |\n| Q3_K_M  | 3.91 | 4.4 | 5.2 | 6.2(6.2,6.2)    | 8.2(8.2,8.2)    | 10.2(10.2,10.2) | 12.2(12.2,12.2) |\n| IQ4_XS  | 4.25 | 4.7 | 5.5 | 6.5(6.5,6.5)    | 8.6(8.6,8.6)    | 10.6(10.6,10.6) | 12.7(12.7,12.7) |\n| Q3_K_L  | 4.27 | 4.7 | 5.5 | 6.5(6.5,6.5)    | 8.6(8.6,8.6)    | 10.7(10.7,10.7) | 12.7(12.7,12.7) |\n| IQ4_NL  | 4.50 | 5.0 | 5.7 | 6.8(6.8,6.8)    | 8.9(8.9,8.9)    | 10.9(10.9,10.9) | 13.0(13.0,13.0) |\n| Q4_0    | 4.55 | 5.0 | 5.8 | 6.8(6.8,6.8)    | 8.9(8.9,8.9)    | 11.0(11.0,11.0) | 13.1(13.1,13.1) |\n| Q4_K_S  | 4.58 | 5.0 | 5.8 | 6.9(6.9,6.9)    | 8.9(8.9,8.9)    | 11.0(11.0,11.0) | 13.1(13.1,13.1) |\n| Q4_K_M  | 4.85 | 5.3 | 6.1 | 7.1(7.1,7.1)    | 9.2(9.2,9.2)    | 11.4(11.4,11.4) | 13.5(13.5,13.5) |\n| Q4_K_L  | 4.90 | 5.3 | 6.1 | 7.2(7.2,7.2)    | 9.3(9.3,9.3)    | 11.4(11.4,11.4) | 13.6(13.6,13.6) |\n| Q5_K_S  | 5.54 | 5.9 | 6.8 | 7.8(7.8,7.8)    | 10.0(10.0,10.0) | 12.2(12.2,12.2) | 14.4(14.4,14.4) |\n| Q5_0    | 5.54 | 5.9 | 6.8 | 7.8(7.8,7.8)    | 10.0(10.0,10.0) | 12.2(12.2,12.2) | 14.4(14.4,14.4) |\n| Q5_K_M  | 5.69 | 6.1 | 6.9 | 8.0(8.0,8.0)    | 10.2(10.2,10.2) | 12.4(12.4,12.4) | 14.6(14.6,14.6) |\n| Q5_K_L  | 5.75 | 6.1 | 7.0 | 8.1(8.1,8.1)    | 10.3(10.3,10.3) | 12.5(12.5,12.5) | 14.7(14.7,14.7) |\n| Q6_K    | 6.59 | 7.0 | 8.0 | 9.4(9.4,9.4)    | 12.2(12.2,12.2) | 15.0(15.0,15.0) | 17.8(17.8,17.8) |\n| Q8_0    | 8.50 | 8.8 | 9.9 | 11.4(11.4,11.4) | 14.4(14.4,14.4) | 17.4(17.4,17.4) | 20.3(20.3,20.3) |\n```\n\nTo find the best quantisation type for a given memory constraint (e.g. 6GB) you can provide `--fits \u003cnumber of GB\u003e`:\n\n```shell\ngollama --vram NousResearch/Hermes-2-Theta-Llama-3-8B --fits 6\n\n📊 VRAM Estimation for Model: NousResearch/Hermes-2-Theta-Llama-3-8B\n\n| QUANT/CTX | BPW  | 2K  | 8K  | 16K          | 32K           | 49K            | 64K             |\n| --------- | ---- | --- | --- | ------------ | ------------- | -------------- | --------------- |\n| IQ1_S     | 1.56 | 2.4 | 3.8 | 5.7(4.7,4.2) | 9.5(7.5,6.5)  | 13.3(10.3,8.8) | 17.1(13.1,11.1) |\n| IQ2_XXS   | 2.06 | 2.9 | 4.3 | 6.3(5.3,4.8) | 10.1(8.1,7.1) | 13.9(10.9,9.4) | 17.8(13.8,11.8) |\n...\n```\n\nThis will display a table showing vRAM usage for various quantisation types and context sizes.\n\nThe vRAM estimator works by:\n\n1. Fetching the model configuration from Hugging Face (if not cached locally)\n2. Calculating the memory requirements for model parameters, activations, and KV cache\n3. Adjusting calculations based on the specified quantisation settings\n4. Performing binary and linear searches to optimize for context length or quantisation settings\n\nNote: The estimator will attempt to use CUDA vRAM if available, otherwise it will fall back to system RAM for calculations.\n\n## Configuration\n\nGollama uses a JSON configuration file located at `~/.config/gollama/config.json`. The configuration file includes options for sorting, columns, API keys, log levels, theme etc...\n\nExample configuration:\n\n```json\n{\n  \"default_sort\": \"modified\",\n  \"columns\": [\n    \"Name\",\n    \"Size\",\n    \"Quant\",\n    \"Family\",\n    \"Modified\",\n    \"ID\"\n  ],\n  \"ollama_api_key\": \"\",\n  \"ollama_api_url\": \"http://localhost:11434\",\n  \"lm_studio_file_paths\": \"\",\n  \"log_level\": \"info\",\n  \"log_file_path\": \"/Users/username/.config/gollama/gollama.log\",\n  \"sort_order\": \"Size\",\n  \"strip_string\": \"my-private-registry.internal/\",\n  \"editor\": \"\",\n  \"docker_container\": \"\"\n}\n```\n\n- `strip_string` can be used to remove a prefix from model names as they are displayed in the TUI. This can be useful if you have a common prefix such as a private registry that you want to remove for display purposes.\n- `docker_container` - **experimental** - if set, gollama will attempt to perform any run operations inside the specified container.\n- `editor` - **experimental** - if set, gollama will use this editor to open the Modelfile for editing.\n- `theme` - **experimental** The name of the theme to use (without .json extension)\n\n## Installation and build from source\n\n1. Clone the repository:\n\n    ```shell\n    git clone https://github.com/sammcj/gollama.git\n    cd gollama\n    ```\n\n2. Build:\n\n    ```shell\n    go get\n    make build\n    ```\n\n3. Run:\n\n    ```shell\n    ./gollama\n    ```\n\n### Themes\n\nGollama has basic customisable theme support, themes are stored as JSON files in `~/.config/gollama/themes/`.\nThe active theme can be set via the `theme` setting in your config file (without the .json extension).\n\nDefault themes will be created if they don't exist:\n\n- `default` - Dark theme with neon accents (default)\n- `light-neon` - Light theme with neon accents, suitable for light terminal backgrounds\n\nTo create a custom theme:\n\n1. Create a new JSON file in the themes directory (e.g. `~/.config/gollama/themes/my-theme.json`)\n2. Use the following structure:\n\n```json\n{\n  \"name\": \"my-theme\",\n  \"description\": \"My custom theme\",\n  \"colours\": {\n    \"header_foreground\": \"#AA1493\",\n    \"header_border\": \"#BA1B11\",\n    \"selected\": \"#FFFFFF\",\n    ...\n  },\n  \"family\": {\n    \"llama\": \"#FF1493\",\n    \"alpaca\": \"#FF00FF\",\n    ...\n  }\n}\n```\n\nColours can be specified as ANSI colour codes (e.g. \"241\") or hex values (e.g. \"#FF00FF\"). The `family` section defines colours for different model families in the list view.\n\n_Note: Using the VSCode extension ['Color Highlight'](https://marketplace.visualstudio.com/items?itemName=naumovs.color-highlight) makes it easier to find the hex values for colours._\n\n## Logging\n\nLogs can be found in the `gollama.log` which is stored in `$HOME/.config/gollama/gollama.log` by default.\nThe log level can be set in the configuration file.\n\n## Contributing\n\nContributions are welcome!\nPlease fork the repository and create a pull request with your changes.\n\n\u003c!-- readme: contributors -start --\u003e\n\u003ctable\u003e\n\t\u003ctbody\u003e\n\t\t\u003ctr\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/sammcj\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/862951?v=4\" width=\"50;\" alt=\"sammcj\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eSam\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/Camsbury\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/7485022?v=4\" width=\"50;\" alt=\"Camsbury\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eCameron Kingsbury\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/KimCookieYa\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/45006957?v=4\" width=\"50;\" alt=\"KimCookieYa\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eKimCookieYa\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/DenisBalan\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/33955091?v=4\" width=\"50;\" alt=\"DenisBalan\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eDenis Balan\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/erg\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/27430?v=4\" width=\"50;\" alt=\"erg\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eDoug Coleman\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/Impact123\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/899193?v=4\" width=\"50;\" alt=\"Impact123\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eImpact\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n\t\t\u003c/tr\u003e\n\t\t\u003ctr\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/josekasna\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/138180151?v=4\" width=\"50;\" alt=\"josekasna\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eJose Almaraz\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/jralmaraz\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/13877691?v=4\" width=\"50;\" alt=\"jralmaraz\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eJose Roberto Almaraz\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/Br1ght0ne\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/12615679?v=4\" width=\"50;\" alt=\"Br1ght0ne\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eOleksii Filonenko\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/southwolf\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/150648?v=4\" width=\"50;\" alt=\"southwolf\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eSouthWolf\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/agustif\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/6601142?v=4\" width=\"50;\" alt=\"agustif\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eagustif\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/anrgct\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/16172523?v=4\" width=\"50;\" alt=\"anrgct\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eanrgct\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n\t\t\u003c/tr\u003e\n\t\t\u003ctr\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003ca href=\"https://github.com/fuho\"\u003e\n                    \u003cimg src=\"https://avatars.githubusercontent.com/u/539452?v=4\" width=\"50;\" alt=\"fuho\"/\u003e\n                    \u003cbr /\u003e\n                    \u003csub\u003e\u003cb\u003eondrej\u003c/b\u003e\u003c/sub\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n\t\t\u003c/tr\u003e\n\t\u003ctbody\u003e\n\u003c/table\u003e\n\u003c!-- readme: contributors -end --\u003e\n\n## Acknowledgements\n\n- [Ollama](https://ollama.com/)\n- [Llama.cpp](https://github.com/ggerganov/llama.cpp)\n- [Charmbracelet](https://charm.sh/)\n- [Spitter](https://github.com/sammcj/spitter) - For model copying functionality\n\nThank you to folks such as Matt Williams, Fahd Mirza and AI Code King for giving this a shot and providing feedback.\n\n[![AI Code King - Easiest \u0026 Interactive way to Manage \u0026 Run Ollama Models Locally](https://img.youtube.com/vi/T4uiTnacyhI/0.jpg)](https://www.youtube.com/watch?v=T4uiTnacyhI)\n[![Matt Williams - My favourite way to run Ollama: Gollama](https://img.youtube.com/vi/OCXuYm6LKgE/0.jpg)](https://www.youtube.com/watch?v=OCXuYm6LKgE)\n[![Fahd Mirza - Gollama - Manage Ollama Models Locally](https://img.youtube.com/vi/24yqFrQV-4Q/0.jpg)](https://www.youtube.com/watch?v=24yqFrQV-4Q)\n\n## License\n\nCopyright © 2024 Sam McLeod\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsammcj%2Fgollama","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsammcj%2Fgollama","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsammcj%2Fgollama/lists"}