Skip to content

Commit d2130ae

Browse files
casteryhallenwang28
authored andcommitted
CI badge should point to main branch (#422)
1 parent 0496edb commit d2130ae

File tree

2 files changed

+5
-3
lines changed

2 files changed

+5
-3
lines changed

.github/workflows/unit_test.yaml

Lines changed: 3 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -2,7 +2,9 @@ name: Unit Tests
22

33
on:
44
pull_request:
5-
5+
push:
6+
branches: [ main ]
7+
workflow_dispatch:
68

79
jobs:
810
unit_tests:

README.md

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1,8 +1,8 @@
11
# <img width="35" height="35" alt="image" src="https://github.com/user-attachments/assets/2700a971-e5d6-4036-b03f-2f89c9791609" /> Forge
22

33
#### A PyTorch-native agentic RL library that lets you focus on algorithms—not infra.
4-
[![Unit Tests](https://github.com/meta-pytorch/forge/actions/workflows/unit_test.yaml/badge.svg)](https://github.com/meta-pytorch/forge/actions/workflows/unit_test.yaml)
5-
[![GPU Tests](https://github.com/meta-pytorch/forge/actions/workflows/gpu_test.yaml/badge.svg)](https://github.com/meta-pytorch/forge/actions/workflows/gpu_test.yaml)
4+
[![Unit Tests](https://github.com/meta-pytorch/forge/actions/workflows/unit_test.yaml/badge.svg?branch=main)](https://github.com/meta-pytorch/forge/actions/workflows/unit_test.yaml?query=branch%3Amain)
5+
[![GPU Tests](https://github.com/meta-pytorch/forge/actions/workflows/gpu_test.yaml/badge.svg?branch=main)](https://github.com/meta-pytorch/forge/actions/workflows/gpu_test.yaml?query=branch%3Amain)
66

77
## Overview
88
The primary purpose of the Forge ecosystem is to delineate infra concerns from model concerns thereby making RL experimentation easier. Forge delivers this by providing clear RL abstractions and one scalable implementation of these abstractions. When you need fine-grained control over placement, fault handling/redirecting training loads during a run, or communication patterns, the primitives are there. When you don’t, you can focus purely on your RL algorithm.

0 commit comments

Comments
 (0)