extract 0 0 0

mlabonne/harmless_alpaca

published by @mlabonne

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
190.2K
Last 30 days
32.1K
Likes
51
Size
1.2 MB
Created on HF
2024-05-28
Age
2 years ago

Tags

language:ensize_categories:10K<n<100Kformat:parquetmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:us

README current version from Hugging Face


language:

  • en
    dataset_info:
    features:
    • name: text
      dtype: string
      splits:
    • name: train
      num_bytes: 1589987
      num_examples: 25058
    • name: test
      num_bytes: 397546
      num_examples: 6265
      download_size: 1215139
      dataset_size: 1987533
      configs:
  • config_name: default
    data_files:
    • split: train
      path: data/train-*
    • split: test
      path: data/test-*

README history 3 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. 2024-05-30Librarian Bot: Add language metadata for dataset (#2)02c6a92388 B
    Loading...
  2. 2024-05-28Upload dataseta927232373 B
    Loading...
  3. 2024-05-28initial commitdfe0eba0 B
    Loading...

Used by abliterated models 30+ in catalog

Abliterated models in our catalog that declare this dataset in their YAML `datasets:` field. Sorted by downloads. This back-reference is unique to abliteration.org: Hugging Face does not surface it.

Bahushruth/Qwen3.6-35B-A3B-abliterated-v4
470.1K dl 13 likes
paperscarecrow/Gemma-4-31B-it-abliterated
127.5K dl 124 likes
prem-research/DeepSeek-V4-Flash-0731-abliterated
789 dl 11 likes
mradermacher/gemma-2-2b-jpn-it-abliterated-17-i1-GGUF
518 dl 1 likes
mradermacher/gemma-2-2b-jpn-it-abliterated-24-i1-GGUF
376 dl 1 likes
mradermacher/gemma-2-2b-jpn-it-abliterated-17-GGUF
290 dl 1 likes
mradermacher/gemma-2-2b-jpn-it-abliterated-18-i1-GGUF
278 dl 1 likes
mradermacher/gemma-2-2b-jpn-it-abliterated-18-GGUF
270 dl 1 likes
mradermacher/gemma-2-2b-jpn-it-abliterated-24-GGUF
167 dl 1 likes
JustinChung1111/Gemma-4-31B-it-abliterated
115 dl 1 likes
paperscarecrow/LFM2.5-1.2B-Instruct-abliterated
100 dl 3 likes
ringusTheImp/darkScribe-daredevil-8B-abliterated
75 dl 2 likes
ymcki/gemma-2-2b-jpn-it-abliterated-18
68 dl 1 likes
kof1467/Gemma-4-31B-it-abliterated
67 dl
ScottzillaSystems/Gemma-4-31B-it-abliterated
67 dl
ymcki/gemma-2-2b-jpn-it-abliterated-24
50 dl 1 likes
ymcki/gemma-2-2b-jpn-it-abliterated-17
49 dl 1 likes
paperscarecrow/LFM2-24B-A2B-Abliterated
44 dl 2 likes
anlord/gemma-4-E2B-it-abliterated
37 dl
ZennyKenny/Daredevil-8B-abliterated
30 dl 1 likes
asswa2/Gemma-4-31B-it-abliterated
27 dl
kepom/Gemma-4-31B-it-abliterated
27 dl
Bahushruth/GLM-5.2-FP8-abliterated
26 dl 21 likes
Bahushruth/gemma-4-E4B-it-abliterated
26 dl
nicoboss/A.X-3.1-abliterated
25 dl
stronman/Gemma-4-31B-it-abliterated
24 dl
gulan28/Hermes-3-Llama-3.1-8B-GGUF-abliterated
23 dl
hlililililili/Gemma-4-31B-it-abliterated
22 dl
Bahushruth/gemma-4-26B-A4B-it-abliterated
21 dl
Bahushruth/gemma-4-31B-it-abliterated
21 dl

Used in recipes 3 of 18 curated recipes reference this dataset

Concrete workflows from the community craft-knowledge survey that call for this corpus. Each links to the full recipe with parameters, tools, expected output, and known failure modes.

Community discussions 3 threads · 2 open · 3 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. 2026-05-03Execution-verified instruction dataset — free previewopen1 💬#3
    Loading...
  2. 2024-05-30PRLibrarian Bot: Add language metadata for datasetmerged1 💬#2
    Loading...
  3. 2024-05-29[bot] Conversion to Parquetopen1 💬#1
    Loading...

Related datasets same stage · extract

Read further

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("mlabonne/harmless_alpaca")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="mlabonne/harmless_alpaca", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/mlabonne/harmless_alpaca
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration