Skip to content

fix: typos #2256

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

fix: typos #2256

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 3 additions & 3 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -21,11 +21,11 @@ TensorOpera® AI (https://TensorOpera.ai) is the next-gen cloud service for LLMs

Highly integrated with TensorOpera open source library, TensorOpera AI provides holistic support of three interconnected AI infrastructure layers: user-friendly MLOps, a well-managed scheduler, and high-performance ML libraries for running any AI jobs across GPU Clouds.

A typical workflow is showing in figure above. When developer wants to run a pre-built job in Studio or Job Store, TensorOpera®Launch swiftly pairs AI jobs with the most economical GPU resources, auto-provisions, and effortlessly runs the job, eliminating complex environment setup and management. When running the job, TensorOpera®Launch orchestrates the compute plane in different cluster topologies and configuration so that any complex AI jobs are enabled, regardless model training, deployment, or even federated learning. TensorOpera®Open Source is unified and scalable machine learning library for running these AI jobs anywhere at any scale.
A typical workflow is shown in the figure above. When developer wants to run a pre-built job in Studio or Job Store, TensorOpera®Launch swiftly pairs AI jobs with the most economical GPU resources, auto-provisions, and effortlessly runs the job, eliminating complex environment setup and management. When running the job, TensorOpera®Launch orchestrates the compute plane in different cluster topologies and configuration so that any complex AI jobs are enabled, regardless of model training, deployment, or even federated learning. TensorOpera®Open Source is unified and scalable machine learning library for running these AI jobs anywhere at any scale.

In the MLOps layer of TensorOpera AI
- **TensorOpera® Studio** embraces the power of Generative AI! Access popular open-source foundational models (e.g., LLMs), fine-tune them seamlessly with your specific data, and deploy them scalably and cost-effectively using the TensorOpera Launch on GPU marketplace.
- **TensorOpera® Job Store** maintains a list of pre-built jobs for training, deployment, and federated learning. Developers are encouraged to run directly with customize datasets or models on cheaper GPUs.
- **TensorOpera® Job Store** maintains a list of pre-built jobs for training, deployment, and federated learning. Developers are encouraged to run directly with customized datasets or models on cheaper GPUs.

In the scheduler layer of TensorOpera AI
- **TensorOpera® Launch** swiftly pairs AI jobs with the most economical GPU resources, auto-provisions, and effortlessly runs the job, eliminating complex environment setup and management. It supports a range of compute-intensive jobs for generative AI and LLMs, such as large-scale training, serverless deployments, and vector DB searches. TensorOpera Launch also facilitates on-prem cluster management and deployment on private or hybrid clouds.
Expand All @@ -37,5 +37,5 @@ In the Compute layer of TensorOpera AI
- **TensorOpera® Open Source** is unified and scalable machine learning library for running these AI jobs anywhere at any scale.

# Contributing
FedML embraces and thrive through open-source. We welcome all kinds of contributions from the community. Kudos to all of <a href="https://github.com/fedml-ai/fedml/graphs/contributors" target="_blank">our amazing contributors</a>!
FedML embraces and thrives through open-source. We welcome all kinds of contributions from the community. Kudos to all of <a href="https://github.com/fedml-ai/fedml/graphs/contributors" target="_blank">our amazing contributors</a>!
FedML has adopted [Contributor Covenant](https://github.com/FedML-AI/FedML/blob/master/CODE_OF_CONDUCT.md).