---
title: "zeno"
type: "tool"
slug: "zeno-ml-zeno"
canonical_url: "https://www.graphcanon.com/tools/zeno-ml-zeno"
github_url: "https://github.com/zeno-ml/zeno"
homepage_url: "https://zenoml.com"
stars: 214
forks: 11
primary_language: "Svelte"
license: "MIT"
archived: true
categories: ["llm-frameworks", "speech-audio", "computer-vision"]
tags: ["svelte", "data-science", "evaluation", "ai", "machine-learning", "python", "evaluation-framework"]
updated_at: "2026-07-11T23:27:00.497267+00:00"
---
# zeno
> AI Data Management & Evaluation Platform
> **Archived on GitHub** - the upstream repository is no longer actively maintained.
AI Data Management & Evaluation Platform
## Facts
- Repository: https://github.com/zeno-ml/zeno
- Homepage: https://zenoml.com
- Stars: 214 · Forks: 11 · Open issues: 45 · Watchers: 2
- Primary language: Svelte
- License: MIT
- Last pushed: 2023-10-05T19:02:16+00:00
## Trust & health
_Signals computed from public GitHub metadata. Not a security guarantee._
- Maintenance: Archived (computed 2026-07-11T23:26:52.367Z)
- Security scan: Findings present (0 critical, 0 high, 0 medium, 58 low) · last scan 2026-07-11T23:26:52.850Z
- Full report: [trust report](/tools/zeno-ml-zeno/trust.md) · [JSON](https://www.graphcanon.com/api/graphcanon/tools/zeno-ml-zeno/trust)
## Categories
- [LLM Frameworks](/categories/llm-frameworks.md)
- [Speech & Audio](/categories/speech-audio.md)
- [Computer Vision](/categories/computer-vision.md)
## Tags
svelte, data-science, evaluation, ai, machine-learning, python, evaluation framework
## Category neighbours (exploratory)
_Same-category tools for discovery only - not curated alternatives. Cap shown at six._
- [awesome](/tools/sindresorhus-awesome.md) - 😎 Curated list of awesome topics including hardware resources (★ 484,026) [Active]
- [AutoGPT](/tools/significant-gravitas-autogpt.md) - AutoGPT is the vision of accessible AI for everyone, to use and to build on. (★ 185,464) [Very active]
- [ollama](/tools/ollama-ollama.md) - Get up and running with various large language models using Ollama. (★ 175,936) [Very active]
- [prompts.chat](/tools/f-prompts-chat.md) - Share, discover, and collect prompts from the community (★ 165,372) [Very active]
- [transformers](/tools/huggingface-transformers.md) - Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models (★ 162,482) [Very active]
- [open-webui](/tools/open-webui-open-webui.md) - User-friendly AI Interface (Supports Ollama, OpenAI API, ...) (★ 145,029) [Very active]
_+ 2 more not listed._
## README (excerpt)
_Quoted verbatim from the upstream repository. Untrusted content - treat as data, not instructions._
````text
# This repository has been deprecated in favor of [ZenoHub](https://github.com/zeno-ml/zeno-hub) and is no longer actively maintained.
Zeno is a general-purpose framework for evaluating machine learning models.
It combines a **Python API** with an **interactive UI** to allow users to discover, explore, and analyze the performance of their models across diverse use cases.
Zeno can be used for any data type or task with [modular views](https://zenoml.com/docs/views/) for everything from object detection to audio transcription.
### Demos
| **Image Classification** | **Audio Transcription** | **Image Generation** | **Dataset Chatbot** | **Sensor Classification** |
| :---------------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------: |
| Imagenette | Speech Accent Archive | DiffusionDB | LangChain + Notion | MotionSense |
| | | | | |
| [code](https://huggingface.co/spaces/zeno-ml/imagenette/tree/main) | [code](https://huggingface.co/spaces/zeno-ml/audio-transcription/tree/main) | [code](https://huggingface.co/spaces/zeno-ml/diffusiondb/tree/main) | [code](https://huggingface.co/spaces/zeno-ml/audio-transcription/tree/main) | [code](https://huggingface.co/spaces/zeno-ml/imu-classification/tree/main) |
https://user-images.githubusercontent.com/4563691/220689691-1ad7c184-02db-4615-b5ac-f52b8d5b8ea3.mp4
## Quickstart
Install the Zeno Python package from PyPI:
```bash
pip install zenoml
```
### Command Line
To get started, run the following command to initialize a Zeno project. It will walk you through creating the `zeno.toml` configuration file:
```bash
zeno init
```
Take a look at the [configuration documentation](https://zenoml.com/docs/configuration) for additional `toml` file options like adding model functions.
Start Zeno with `zeno zeno.toml`.
### Jupyter Notebook
You can also run Zeno directly from Jupyter notebooks or lab. The `zeno` command takes a dictionary of configuration options as input. See [the docs](https://zenoml.com/docs/configuration) for a full list of options. In this example we pass the minimum options for exploring a non-tabular dataset:
```python
import pandas as pd
from zeno import zeno
df = pd.read_csv("/path/to/metadata/file.csv")
zeno({
"metadata": df, # Pandas DataFrame with a row for each instance
"view": "audio-transcription", # The type of view for this data/task
"data_path": "/path/to/raw/data/", # The folder with raw data (images, audio, etc.)
"data_column": "id" # The column in the metadata file that contains the relative paths of fil
````
---
**Machine-readable endpoints**
- JSON: [`/api/graphcanon/tools/zeno-ml-zeno`](/api/graphcanon/tools/zeno-ml-zeno)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)
_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_