Train acoustic foundation models on HPC
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 42/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- python
- Domain
- hpc, machine-learning
Research direction
Start with the issue checklist and verify the process for obtaining access to USGS HPC Tallgrass. Then determine how this repository invokes LightlyTrain for EfficientNetV3 Small and MobileNet V3; done means access is available and both models have been trained successfully.
Written by the indexing model from the issue text.
Description
- Get access to USGS HPC Tallgrass
- Train EfficientNetV3 Small and MobileNet V3 models with LightlyTrain
- Dominant language
- Python
- Stars
- 10
- Forks
- 3
- Avg merge
- 5d 13h
- Merged PRs (30d)
- 2
Getting set up
Starts the project's dev container in your browser, under your own GitHub account.
- Ships a Dockerfile or Docker Compose file
- No pull request template
- No contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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Difficulty 5/5 Over a week Newbie friendliness 35/100
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Difficulty 4/5 3-5 days Newbie friendliness 30/100
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