Comments (3)
mauriceweber
commented on August 15, 2024
2
we used a machine with 64 cores and 512GB RAM and it took about 2-3 days for one CC dump to process with the cc_net pipeline. You can expect another day for deduplication and applying the quality classifier.
You can use the quality classifier that we have trained, so that you don't have to retrain it (this part of the readme points you the model).
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newbietuan
commented on August 15, 2024
hello, how much the disk space will need? about 100T?
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kimcando
commented on August 15, 2024
@mauriceweber a single machine with 64 cores and 512 GB? for a single index?
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Related Issues (20)
- Recommended way to load wget-downloaded data using HF datasets API? HOT 1
- Invalid uri: ParseResult(...) must be of the form s3://<bucket>/<key> or file://<path>
- Unavailable Parameters
- Running full pipeline on a small part of CC
- Running the pipeline on cloud or a big data platform HOT 1
- About the final result HOT 2
- What purpose cutoff.csv used in the cc_net pipeline? HOT 2
- Step 2) "Invalid option: ---input_base_uri" HOT 1
- Potential Language Contamination Inquiry HOT 1
- Spanish artifact building error HOT 2
- Inconsistent IDs lead to distributed computing woes. HOT 1
- Train a new wikiref model HOT 1
- Thresholds for all quality signals HOT 1
- Other language data HOT 2
- Impossible unpack tail data... took time to download, but impossible to unpack dataset without quality signals with broken link. HOT 1
- Are shards randomly created? HOT 1
- What is the output of `run_lsh.py`? HOT 8
- possibly missing shard from host HOT 2
- Is there a specific meaning of the snapshot id? HOT 2
- what's the specific meaning of dsir? HOT 4
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