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Showing 2 resources for "pytorch"
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Rollout signal scan

2 rollout risk signals in current results

Biggest gaps: package integrity, install payload. 0 entries have 2+ required gaps.

2 scanned

Install payload

Install payload is sparse; verify before rollout decisions.

risk

0% (0/2)

Adoption queue

Browse adoption queue · balanced

0/2 visible results are ready for staged adoption under this preset.

ready 0caution 2hold 0

Hugging Face Accelerate

1 blockers: Install payload

caution

50/100

Add install/config payload for reproducible team rollout.

Collect package checksum or signed artifact information.

tools/hugging-face-accelerate · trust review · confidence 67%

Hugging Face Diffusers

1 blockers: Install payload

caution

50/100

Add install/config payload for reproducible team rollout.

Collect package checksum or signed artifact information.

tools/hugging-face-diffusers · trust review · confidence 67%

Decision confidence

Decision confidence scan · balanced

0/2 results are high-confidence for the selected preset.

high 0medium 2low 0

Hugging Face Accelerate

Address Package integrity, Install payload before broader rollout.

medium

50/100

Missing: Package integrityMissing: Install payload

tools/hugging-face-accelerate · trust review

Hugging Face Diffusers

Address Package integrity, Install payload before broader rollout.

medium

50/100

Missing: Package integrityMissing: Install payload

tools/hugging-face-diffusers · trust review

Freshness distribution

Current results are broadly fresh

Median age 45 days; all 2 scanned entries are within 90 days.

median 45d

Aging

91–180 days

0%

0 entries

Stale

> 180 days

0%

0 entries

Hugging Face logo
Hugging Face Accelerateby Hugging Face · submitted by oktofeesh1

Apache-2.0 library for running raw PyTorch training and inference code across CPU, GPU, TPU, DeepSpeed, FSDP, and mixed-precision environments.

Hugging Face logo
Hugging Face Diffusersby Hugging Face · submitted by oktofeesh1

Apache-2.0 library for pretrained diffusion model pipelines, schedulers, adapters, optimization, and training workflows for image, video, and audio generation in PyTorch.