> ## Documentation Index
> Fetch the complete documentation index at: https://anaconda.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Models

## Browsing models

Anaconda hosts a <Tooltip tip="Any storage location from which software or software assets, like packages, can be retrieved and installed on a local computer.">repository</Tooltip> of open-source and partner models that you can explore and use to test and develop your applications.

<Tip>
  Use the search function to locate models by name.

  <Frame>
    <img src="https://mintcdn.com/anaconda-29683c67/L9avxgVHHWvs6LTX/images/ai_nav_search_models.png?fit=max&auto=format&n=L9avxgVHHWvs6LTX&q=85&s=ccf39399a0916c1b1dcc0ccc8a6e02ce" alt="models page search box" width="1922" height="723" data-path="images/ai_nav_search_models.png" />
  </Frame>
</Tip>

### Model views

<Tabs>
  <Tab title="Tile view">
    The tile view displays a list of models in a grid, listed alphabetically. Each tile displays the model's name, publisher, model type, a brief description (if available), a <Tooltip tip="Quantization reduces a model's parameter precision to improve memory efficiency or accuracy. It's like condensing a 300-page manual to 50 pages of essential information.">quantization</Tooltip> dropdown, and the model's resource requirements.

    <Frame>
      <img src="https://mintcdn.com/anaconda-29683c67/YGtija9HXl-k020Y/images/ai_nav_tile_view.png?fit=max&auto=format&n=YGtija9HXl-k020Y&q=85&s=d7ce7cd0e851e386c69be0be4056f3ca" alt="models page tile view" width="1922" height="1082" data-path="images/ai_nav_tile_view.png" />
    </Frame>
  </Tab>

  <Tab title="Chart view">
    Use the <Icon icon="chart-scatter-bubble" iconType="solid" /> **Chart** view to visually compare a model's file size or memory requirements against its performance rating for multiple industry-standard evaluation benchmarks to identify the optimal balance between performance and resource requirements.

    To open the chart view, click <Icon icon="chart-scatter-bubble" iconType="solid" /> **Chart** in the upper-right corner of the model browser.

    Each data point in the chart represents a specific quantization level of a model. Hover over a point to view a model's name, quantization level, evaluation score, and file size. Click any point to view the [model's details](/tools/ai-navigator/user-guide/models#viewing-model-details).

    <Tip>
      Scroll to zoom in and out of the chart view to make it easier to hover over and select a specific model from a cluster of similarly ranked models. Click and drag to pan across the chart.
    </Tip>

    * **Y-Axis** options:
      * **HellaSwag**: Evaluates how well a model selects the most natural and logical continuation of everyday scenarios.
      * **WinoGrande**: Evaluates a model's ability to resolve ambiguity by tracking entities across complex linguistic contexts.
      * **TruthfulQA**: Evaluates a model's ability to provide factually accurate responses when asked questions designed to elicit common misconceptions.

    * **X-Axis** options:
      * **Max RAM (GB)**: The maximum amount of RAM the model requires.
      * **Model Size (GB)**: How much disk space the model requires.

    <Frame>
      <img src="https://mintcdn.com/anaconda-29683c67/ZgqdN7i1L1qurUKy/images/ai_nav_chart_view.gif?s=acdf0bab57b4f917eb50190ca743417e" alt="animated models page chart view interactions" width="1273" height="714" data-path="images/ai_nav_chart_view.gif" />
    </Frame>
  </Tab>
</Tabs>

### Model types

Anaconda AI Navigator currently supports the following types of models:

`text-generation`: Designed to produce coherent and contextually relevant natural language based on user input. Common use cases for `text-generation` models are:

* **Content Creation**: Drafting articles, outlines, summaries, or creative pieces
* **Coding Assistance**: Generating or autocompleting code and troubleshooting issues
* **Data Extraction**: Summarizing and interpreting large datasets to uncover insights
* **Conversational AI**: Driving chatbots and virtual assistants to create "human-like" dialogue

`sentence-similarity`: Encodes text into a vector database (embedding) that captures semantic meaning. These embeddings enable efficient comparison and analysis of text based on contextual relationships. Common use cases for `sentence-similarity` models are:

* **Semantic Search**: Finding documents or items contextually similar to a query, beyond keyword matching
* **Recommendation Systems**: Suggesting relevant items by comparing semantic similarity to user preferences
* **Text Classification**: Categorizing text (for example, spam detection, sentiment analysis) based on meaning
* **Clustering Analysis**: Grouping similar text data to uncover patterns or organize information

[Contact us if you are interested in specific models or use cases](https://docs.google.com/forms/d/e/1FAIpQLSfOOUTjMJpMdIuEZddcTCht5MqI4t-FcfPDfRj671X0V8H-QQ/viewform?usp=sf_link).

## Filtering models

Apply filters to help you find the models that you want to use.

<Tip>
  Filters can be applied in both the tile and chart views.
</Tip>

To apply a filter:

1. From the <Icon icon="brain-circuit" iconType="light" /> **Models** page, click <Icon icon="filter" iconType="light" /> **Filter**.
2. Add or adjust a filter to narrow down the list of models.
3. Repeat as necessary to list only the models you want.

### Model filters

* **Publisher**: Filter models by the organization that built them.
* **Quantization**: Filter models by the quantization method used to build them.
* **File Size**: Adjust the slider to filter models by the amount of disk space they require.
* **RAM**: Adjust the slider to filter models by the amount of RAM they require.
* **License**: Filter models based on their usage, modification, and distribution terms.
* **Date Published**: Filter models based on the date they were published to AI Navigator. Click <Icon icon="arrows-rotate" iconType="regular" /> **Refresh** to reset the currently applied date filter.
* **Purpose**: Filter models based on their associated [model type](#model-types).
* **Language**: Filter models by which spoken languages they can understand.
* **Only Show Compatible Models**: Filters out models that require more memory than your system's RAM+VRAM can provide. Enabled by default.

<Note>
  Click the <Icon icon="circle-x" iconType="solid" /> icon beside any filter to remove it, or click **Clear** in the  <Icon icon="filter" iconType="light" /> **All Filters** panel to clear all filters at once.

  Range filters (**File Size** and **RAM**) can be reset by dragging the slider to fill the entire range.
</Note>

<Frame>
  <img src="https://mintcdn.com/anaconda-29683c67/L9avxgVHHWvs6LTX/images/ai_nav_model_filters.png?fit=max&auto=format&n=L9avxgVHHWvs6LTX&q=85&s=9e767dc276ce6a934ea2a8c745b1e2ff" alt="models page right-hand filters panel" width="1922" height="1082" data-path="images/ai_nav_model_filters.png" />
</Frame>

## Downloading models

Anaconda provides a variety of LLM models for you to work with, constructed at various levels of [quantization](/reference/glossary#quantization-method).

To download a model:

1. Select <Icon icon="brain-circuit" iconType="light" /> **Models** from the left-hand navigation.
2. Locate a model you want to download.
3. Open the **Quantization Method** dropdown and select a file quantization level, then click <Icon icon="arrow-down-to-line" iconType="regular" /> **Download** to download the model locally.

   <Frame>
     <img src="https://mintcdn.com/anaconda-29683c67/L9avxgVHHWvs6LTX/images/ai_nav_model_quant_method.png?fit=max&auto=format&n=L9avxgVHHWvs6LTX&q=85&s=0ad136799fb9ff14dc7900e5928dcfe5" alt="models tile view quant method dropdown" width="3460" height="2164" data-path="images/ai_nav_model_quant_method.png" />
   </Frame>

   <Note>
     Models that show a **Downloaded** tag on their tile indicate that you have downloaded at least one file for that model.
   </Note>

## Managing downloads

Manage your downloads using the <Icon icon="pause" iconType="solid" /> **pause**, <Icon icon="play" iconType="solid" /> **play**, or <Icon icon="ban" iconType="regular" /> **cancel** buttons beside the progress bar at the bottom of the model's tile.

<Tip>
  * You can also manage your downloads from the <Icon icon="download" iconType="regular" /> **My Models** page.
  * Downloads automatically pause if you exit the application for any reason.
</Tip>

<Frame>
  <img src="https://mintcdn.com/anaconda-29683c67/YGtija9HXl-k020Y/images/ai_nav_tile_download_controls.png?fit=max&auto=format&n=YGtija9HXl-k020Y&q=85&s=520e2ed567f0970765a8b21c582fab51" alt="models tile view download controls" width="1922" height="1082" data-path="images/ai_nav_tile_download_controls.png" />
</Frame>

## Deleting models

To delete models that you have downloaded, navigate to the <Icon icon="download" iconType="regular" /> **My Models** page and click <Icon icon="trash-can" iconType="regular" /> **Delete** beside the model. If you have more than one file downloaded for a model, select a file to delete from the model's dropdown first.

<Note>
  Models cannot be deleted while they're loaded into the chat interface or the API server.
</Note>

## Viewing model details

Click on a model's tile to view its details. From here, you can read a brief description of the model and see important information about it, such as its file size at each quantization level, <Tooltip tip="Model parameters are the weights and biases it learns during training. The more parameters a model has, the better its ability to learn, but the more tightly it will conform to its training data.">parameter</Tooltip> count, the quality you can expect from the model's output, how much resource usage can be expected by the model, and its intended purpose (for use in either development or production).

<Frame>
  <img src="https://mintcdn.com/anaconda-29683c67/YGtija9HXl-k020Y/images/ai_nav_model_details.png?fit=max&auto=format&n=YGtija9HXl-k020Y&q=85&s=f5ca7c2803f2c8fda2e76f5c9404e9cd" alt="model details view" width="1922" height="1082" data-path="images/ai_nav_model_details.png" />
</Frame>

<Tip>
  * Hover over a <Icon icon="circle-info" iconType="regular" /> tooltip to view detailed information about the various aspects of a model.
  * Click **Learn more** <Icon icon="arrow-up-right-from-square" iconType="regular" /> to visit the Huggingface webpage of the organization that built the model.
</Tip>
