Clip-as-a-service
github.com/jina-ai/clip-as-serviceCLIP-as-service provides scalable image and sentence embeddings, reasoning, and ranking with CLIP.
Looking for something like Mahout? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 22 are open source.
Apache Mahout develops Qumat, a backend agnostic quantum circuit library, and QDP, a GPU accelerated quantum data encoding engine.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Clip-as-a-service | — | Not stated | — |
| 2 | Datumbox | — | Yes | — |
| 3 | Hypernets | — | Yes | — |
| 4 | Kale | — | Yes | — |
| 5 | ClearML | — | Yes | — |
| 6 | Kedro-Viz | — | Yes | — |
| 7 | ClearML | — | Yes | — |
| 8 | Featureform | — | Yes | — |
| 9 | LLM App | — | Yes | — |
| 10 | Feast | — | Yes | Web |
CLIP-as-service provides scalable image and sentence embeddings, reasoning, and ranking with CLIP.
The Datumbox framework is written in Java for developing machine learning and statistical applications.
Hypernets offers a general automated machine learning framework for developing end to end AutoML toolkits in specific domains.
Kale simplifies data science workflows for deploying Kubeflow Pipelines.
ClearML combines experiment and data management, pipelines, scheduling, orchestration, and model serving for AI workloads.
Kedro-Viz visualizes Kedro data and machine learning pipelines and tracks experiments.
ClearML manages AI experiments, data, pipelines, orchestration, scheduling, and model serving in one MLOps platform.
Featureform turns existing data infrastructure into a virtual feature store.
Pathway offers cloud templates for RAG, AI pipelines, and enterprise search that stay synchronized with connected data sources.
The open source Feast feature store lets teams define, manage, discover, and serve features for machine learning.
TensorFlow offers an open-source machine learning platform with tools, libraries, and community resources.
Build neural networks and support machine learning research with Sonnet, a library based on TensorFlow.
FLAML provides a fast Python library for automated machine learning and tuning.
The fuku-ml project provides a machine learning library described as simple to use.
FlexML offers an easy to use and flexible automated machine learning library for Python.
Burn provides a flexible, efficient, and portable tensor library for building deep learning applications.
The goro project provides a high level machine learning library written for Go.
PyTorch Ignite provides a high level library for flexibly training and evaluating neural networks.
Lucent brings the Lucid library approach to PyTorch, according to its repository description.
Apache SINGA supports distributed deep learning through a system and library for model training.
Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
Catniff provides JavaScript developers with a Torch-like deep learning framework.
Sagify describes its project as a way to work with large language models and machine learning more easily.
TPOT uses genetic programming to optimize machine learning pipelines in Python.
Alternatives are suggested from the purpose and features described in our listings. Different pages for the same product appear once. Read each description to check whether it fits your task. How we choose alternatives · Suggest an alternative