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ai-ml / prodigy-plus-schedule-free
Install & Compatibility
Where this runs
tested against v2.0.1 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.95 runs
build_error
glibcpy 3.10–3.95 runs
installs and imports cleanly · install 76.2s · import 0.000s · 4710.4MB
5140MB installed
● package 5140MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
ProdigyPlusScheduleFree
✓ from prodigy_plus_schedule_free import ProdigyPlusScheduleFree
✗ from prodigy_plus_schedule_free import ProdigyPlusScheduleFree
Common mistake: using 'prodigyplus' instead of 'prodigy_plus_schedule_free'.
Basic usage: instantiate optimizer, call .train() before training loop, step normally.
import torch
from prodigy_plus_schedule_free import ProdigyPlusScheduleFree
model = torch.nn.Linear(10, 2)
optimizer = ProdigyPlusScheduleFree(model.parameters(), lr=1.0)
optimizer.train()
for data, target in [(torch.randn(10), torch.tensor(1))]:
optimizer.zero_grad()
loss = torch.nn.functional.cross_entropy(model(data), target.unsqueeze(0))
loss.backward()
optimizer.step()
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Version history
2.0.1latest on PyPI · released Sep 27, 2025
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Dependencies
torchrequiredPyTorch is required for optimizers and tensors.