# Guides

## Introduction

To get started with Tensorleap, we provided a few step-by-step guides, describing an integration of datasets and models, in addition to various analyses.

#### Integrating the Dataset and Model

The first step to getting started with Tensorleap is to integrate your datasets and models. This can be done through the [**Integration Script**](/tensorleap-integration/writing-integration-code.md), which defines how to read each sample and metadata. 

There are multiple ways to integrate your model:

* **Pre-Trained** - You can import a pre-trained model through the [**Import Model**](/user-interface/project/versions/import-model.md) feature or through the [**CLI Model Integration**](/getting-started/quickstart/quickstart-using-cli.md#model-integration). After the model and dataset are imported, you must [**Evaluate the Model**](/user-interface/project/menu-bar/evaluate-a-model.md#evaluate-model) (inference) in order to get the metrics and analyses. 
* **Built from Scratch** - Some users prefer building the model and altering it in the [**Network View**](/user-interface/project/network.md). Then the model is Trained within the platform. 

In the full-guides below, we present both cases for each use-case.

{% hint style="info" %}
Tensorleap is now available for a **free trial**! For more info, see [**Try Tensorleap for Free**](broken://pages/reHfp80krQ2R6gWEaNyr).
{% endhint %}

## Full Guides

Guides are designed to get you started quickly with Tensorleap.

Choose one to get started:

* [**MNIST - Image Classification**](/guides/full-guides/mnist-guide.md) - integration, training, analysis and metrics.

![Sample's Details](/files/AN5jMfKP5vRfmRm8lKeG) ![Fetch Similars](/files/9fCPf2ifS8gJ8nhxH85S) ![Similar Samples Heat Map](/files/XESbIzFUyRoin1AtcccJ)

* [**IMDB - Semantic Text classification**](/guides/full-guides/imdb-guide.md) - integration, training, analysis and metrics.

![Heat map for Negative Output](/files/VJXyZAesqQ0gaWLcNl2x) ![Metrics Dashboard](/files/AgN4RjW2TbmJyPa0SHkG)

### Dataset Script

#### Guide

 A guide about the Dataset Script can be found [**here**](/tensorleap-integration/writing-integration-code.md).

#### Examples

* [**Wikipedia Toxicity (using Tensorflow Datasets**](/tensorleap-integration/writing-integration-code/examples/wikipedia-toxicity-using-tensorflow-datasets.md)**)**
* [**CelebA (using Google Cloud Storage)**](/tensorleap-integration/writing-integration-code/examples/celeba-classification-using-gcs.md)

{% hint style="info" %}
The [**Reference**](/user-interface.md) documentation for the Tensorleap user interface (UI) and Command Line Interface (CLI) may prove useful when going through these tutorials.
{% endhint %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.tensorleap.ai/guides.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.