+++ disableToc = false title = "🖼️ Model gallery" weight = 7 +++




The model gallery is a (experimental!) collection of models configurations for [LocalAI](https://github.com/go-skynet/LocalAI). LocalAI to ease out installations of models provide a way to preload models on start and downloading and installing them in runtime. You can install models manually by copying them over the `models` directory, or use the API to configure, download and verify the model assets for you. As the UI is still a work in progress, you will find here the documentation about the API Endpoints. {{% notice note %}} The models in this gallery are not directly maintained by LocalAI. If you find a model that is not working, please open an issue on the model gallery repository. {{% /notice %}} {{% notice note %}} GPT and text generation models might have a license which is not permissive for commercial use or might be questionable or without any license at all. Please check the model license before using it. The official gallery contains only open licensed models. {{% /notice %}} ## Useful Links and resources - [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) - here you can find a list of the most performing models on the Open LLM benchmark. Keep in mind models compatible with LocalAI must be quantized in the `gguf` format. ## Model repositories You can install a model in runtime, while the API is running and it is started already, or before starting the API by preloading the models. To install a model in runtime you will need to use the `/models/apply` LocalAI API endpoint. To enable the `model-gallery` repository you need to start `local-ai` with the `GALLERIES` environment variable: ``` GALLERIES=[{"name":"", "url":"" }' # or if from a repository curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{ "id": "@" }' ``` An example that installs openllama can be: ```bash LOCALAI=http://localhost:8080 curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{ "url": "https://github.com/go-skynet/model-gallery/blob/main/openllama_3b.yaml" }' ``` The API will return a job `uuid` that you can use to track the job progress: ``` {"uuid":"1059474d-f4f9-11ed-8d99-c4cbe106d571","status":"http://localhost:8080/models/jobs/1059474d-f4f9-11ed-8d99-c4cbe106d571"} ``` For instance, a small example bash script that waits a job to complete can be (requires `jq`): ```bash response=$(curl -s http://localhost:8080/models/apply -H "Content-Type: application/json" -d '{"url": "$model_url"}') job_id=$(echo "$response" | jq -r '.uuid') while [ "$(curl -s http://localhost:8080/models/jobs/"$job_id" | jq -r '.processed')" != "true" ]; do sleep 1 done echo "Job completed" ``` To preload models on start instead you can use the `PRELOAD_MODELS` environment variable.
To preload models on start, use the `PRELOAD_MODELS` environment variable by setting it to a JSON array of model uri: ```bash PRELOAD_MODELS='[{"url": ""}]' ``` Note: `url` or `id` must be specified. `url` is used to a url to a model gallery configuration, while an `id` is used to refer to models inside repositories. If both are specified, the `id` will be used. For example: ```bash PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/stablediffusion.yaml"}] ``` or as arg: ```bash local-ai --preload-models '[{"url": "github:go-skynet/model-gallery/stablediffusion.yaml"}]' ``` or in a YAML file: ```bash local-ai --preload-models-config "/path/to/yaml" ``` YAML: ```yaml - url: github:go-skynet/model-gallery/stablediffusion.yaml ```
{{% notice note %}} You can find already some open licensed models in the [model gallery](https://github.com/go-skynet/model-gallery). If you don't find the model in the gallery you can try to use the "base" model and provide an URL to LocalAI:
``` curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{ "url": "github:go-skynet/model-gallery/base.yaml", "name": "model-name", "files": [ { "uri": "", "sha256": "", "filename": "model" } ] }' ```
{{% /notice %}} ## Installing a model with a different name To install a model with a different name, specify a `name` parameter in the request body. ```bash LOCALAI=http://localhost:8080 curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{ "url": "", "name": "" }' ``` For example, to install a model as `gpt-3.5-turbo`: ```bash LOCALAI=http://localhost:8080 curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{ "url": "github:go-skynet/model-gallery/gpt4all-j.yaml", "name": "gpt-3.5-turbo" }' ``` ## Additional Files
To download additional files with the model, use the `files` parameter: ```bash LOCALAI=http://localhost:8080 curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{ "url": "", "name": "", "files": [ { "uri": "", "sha256": "", "filename": "" } ] }' ```
## Overriding configuration files
To override portions of the configuration file, such as the backend or the model file, use the `overrides` parameter: ```bash LOCALAI=http://localhost:8080 curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{ "url": "", "name": "", "overrides": { "backend": "llama", "f16": true, ... } }' ```
## Examples ### Embeddings: Bert
```bash curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{ "url": "github:go-skynet/model-gallery/bert-embeddings.yaml", "name": "text-embedding-ada-002" }' ``` To test it: ```bash LOCALAI=http://localhost:8080 curl $LOCALAI/v1/embeddings -H "Content-Type: application/json" -d '{ "input": "Test", "model": "text-embedding-ada-002" }' ```
### Image generation: Stable diffusion URL: https://github.com/EdVince/Stable-Diffusion-NCNN {{< tabs >}} {{% tab name="Prepare the model in runtime" %}} While the API is running, you can install the model by using the `/models/apply` endpoint and point it to the `stablediffusion` model in the [models-gallery](https://github.com/go-skynet/model-gallery#image-generation-stable-diffusion): ```bash curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{ "url": "github:go-skynet/model-gallery/stablediffusion.yaml" }' ``` {{% /tab %}} {{% tab name="Automatically prepare the model before start" %}} You can set the `PRELOAD_MODELS` environment variable: ```bash PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/stablediffusion.yaml"}] ``` or as arg: ```bash local-ai --preload-models '[{"url": "github:go-skynet/model-gallery/stablediffusion.yaml"}]' ``` or in a YAML file: ```bash local-ai --preload-models-config "/path/to/yaml" ``` YAML: ```yaml - url: github:go-skynet/model-gallery/stablediffusion.yaml ``` {{% /tab %}} {{< /tabs >}} Test it: ``` curl $LOCALAI/v1/images/generations -H "Content-Type: application/json" -d '{ "prompt": "floating hair, portrait, ((loli)), ((one girl)), cute face, hidden hands, asymmetrical bangs, beautiful detailed eyes, eye shadow, hair ornament, ribbons, bowties, buttons, pleated skirt, (((masterpiece))), ((best quality)), colorful|((part of the head)), ((((mutated hands and fingers)))), deformed, blurry, bad anatomy, disfigured, poorly drawn face, mutation, mutated, extra limb, ugly, poorly drawn hands, missing limb, blurry, floating limbs, disconnected limbs, malformed hands, blur, out of focus, long neck, long body, Octane renderer, lowres, bad anatomy, bad hands, text", "mode": 2, "seed":9000, "size": "256x256", "n":2 }' ``` ### Audio transcription: Whisper URL: https://github.com/ggerganov/whisper.cpp {{< tabs >}} {{% tab name="Prepare the model in runtime" %}} ```bash curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{ "url": "github:go-skynet/model-gallery/whisper-base.yaml", "name": "whisper-1" }' ``` {{% /tab %}} {{% tab name="Automatically prepare the model before start" %}} You can set the `PRELOAD_MODELS` environment variable: ```bash PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/whisper-base.yaml", "name": "whisper-1"}] ``` or as arg: ```bash local-ai --preload-models '[{"url": "github:go-skynet/model-gallery/whisper-base.yaml", "name": "whisper-1"}]' ``` or in a YAML file: ```bash local-ai --preload-models-config "/path/to/yaml" ``` YAML: ```yaml - url: github:go-skynet/model-gallery/whisper-base.yaml name: whisper-1 ``` {{% /tab %}} {{< /tabs >}} ### GPTs
```bash LOCALAI=http://localhost:8080 curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{ "url": "github:go-skynet/model-gallery/gpt4all-j.yaml", "name": "gpt4all-j" }' ``` To test it: ``` curl $LOCALAI/v1/chat/completions -H "Content-Type: application/json" -d '{ "model": "gpt4all-j", "messages": [{"role": "user", "content": "How are you?"}], "temperature": 0.1 }' ```
### Note LocalAI will create a batch process that downloads the required files from a model definition and automatically reload itself to include the new model. Input: `url` or `id` (required), `name` (optional), `files` (optional) ```bash curl http://localhost:8080/models/apply -H "Content-Type: application/json" -d '{ "url": "", "id": "@", "name": "", "files": [ { "uri": "", "sha256": "", "filename": "" }, "overrides": { "backend": "...", "f16": true } ] } ``` An optional, list of additional files can be specified to be downloaded within `files`. The `name` allows to override the model name. Finally it is possible to override the model config file with `override`. The `url` is a full URL, or a github url (`github:org/repo/file.yaml`), or a local file (`file:///path/to/file.yaml`). The `id` is a string in the form `@`, where `` is the name of the gallery, and `` is the name of the model in the gallery. Galleries can be specified during startup with the `GALLERIES` environment variable. Returns an `uuid` and an `url` to follow up the state of the process: ```json { "uuid":"251475c9-f666-11ed-95e0-9a8a4480ac58", "status":"http://localhost:8080/models/jobs/251475c9-f666-11ed-95e0-9a8a4480ac58"} ``` To see a collection example of curated models definition files, see the [model-gallery](https://github.com/go-skynet/model-gallery). #### Get model job state `/models/jobs/` This endpoint returns the state of the batch job associated to a model installation. ```bash curl http://localhost:8080/models/jobs/ ``` Returns a json containing the error, and if the job is being processed: ```json {"error":null,"processed":true,"message":"completed"} ```