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rombodawg/LosslessMegaCodeTrainingV2

published by @rombodawg

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
1.9K
Last 30 days
36
Likes
20
Size
1.4 GB
Created on HF
2023-08-05
Age
3 years ago

Description

VERSION 3 IS RELEASED DOWNLOAD HERE:

https://huggingface.co/datasets/rombodawg/LosslessMegaCodeTrainingV3_2.2m_Evol

Updated/Uncensored version 1 here: https://huggingface.co/datasets/rombodawg/2XUNCENSORED_MegaCodeTraining188k

Non-code instruct training here: https://huggingface.co/datasets/rombodawg/2XUNCENSORED_alpaca_840k_Evol_USER_ASSIS

Legacy version 1 code training here: https://huggingface.co/datasets/rombodawg/MegaCodeTraining200k

This is the ultimate code training data, created to… See the full description on the dataset page: https://huggingface.co/datasets/rombodawg/LosslessMegaCodeTrainingV2.

Tags

license:othersize_categories:100K<n<1Mformat:jsonmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:us

README current version from Hugging Face


license: other


VERSION 3 IS RELEASED DOWNLOAD HERE:


Updated/Uncensored version 1 here: https://huggingface.co/datasets/rombodawg/2XUNCENSORED_MegaCodeTraining188k

Non-code instruct training here: https://huggingface.co/datasets/rombodawg/2XUNCENSORED_alpaca_840k_Evol_USER_ASSIS

Legacy version 1 code training here: https://huggingface.co/datasets/rombodawg/MegaCodeTraining200k

This is the ultimate code training data, created to be lossless so the AI model does not lose any other abilities that it had previously (such as logical skills) after training on this dataset.

The reason why this dataset is so large is so that as the model learns to code, it continues to remember to follow regular instructions as to not lose previously learned abilities.

This is the outcome of all my work gathering data, testing AI models, and discovering what, why, and how coding models do and don't perform well.

If non of this is making any sense think of it this way, I took the old MegaCoding dataset, added like 8x more data that is purely instruction based (non coding), then ran a script to remove a ton (literally 10's of thousands of lines of instructions) that was deemed to be censored. This dataset is the result of that process.

This dataset is the combination of my 2 previous datasets found below:

Coding:

https://huggingface.co/datasets/rombodawg/2XUNCENSORED_MegaCodeTraining188k

Instruction following:

https://huggingface.co/datasets/rombodawg/2XUNCENSORED_alpaca_840k_Evol_USER_ASSIST

README history 14 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

  1. 2023-08-16Update README.mdb3665a21.7 KB
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  5. 2023-08-05Upload DeDuped_LosslessMegaCodeTrainingV2_942k_Evol_Uncensored.jsona3a387d1.1 KB
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  6. 2023-08-05Delete LosslessMegaCodeTrainingV2_1m_Evol_Uncensored.json25afc281.1 KB
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  9. 2023-08-05Upload LosslessMegaCodeTrainingV2_1m_Evol_Uncensored.jsonada294b812 B
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  10. 2023-08-05Update README.md633ccac812 B
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  14. 2023-08-05initial commit1ae269923 B
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Used by abliterated models none yet

No abliterated models in our catalog have declared this dataset in their YAML metadata yet. This can mean the dataset is used but not declared, is used outside abliteration workflows, or is new. The link will populate automatically as models are indexed.

Community discussions 3 threads · 3 open · 7 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

  1. 2024-01-07[bot] Conversion to Parquetopen1 💬#3
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  2. 2023-08-15Incomporate bigcode commitpackftopen2 💬#2
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  3. 2023-08-05Lucky timing!!open4 💬#1
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Metadata

License
other

Repository

Download the dataset

0

Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)
from datasets import load_dataset
ds = load_dataset("rombodawg/LosslessMegaCodeTrainingV2")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="rombodawg/LosslessMegaCodeTrainingV2", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/rombodawg/LosslessMegaCodeTrainingV2
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