fine-tune 0 0 0

anton96vice/samantha-1.1-uncensored-split-and-prepared

published by @anton96vice

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
628
Last 30 days
13
Likes
1
Size
6.1 MB
Created on HF
2024-03-07
Age
2 years ago

Description

Dataset Card for Dataset Name

Samantha-1.1-instructed-uncensored prepared for training

Dataset Details

Dataset Description

This dataset comprises a rich collection of uncensored, instruction-based interactions with Samantha, a virtual assistant designed to perform tasks based on textual commands. Each entry is a detailed record of an instruction provided to Samantha, the input she received, and the output she produced, accompanied by additional… See the full description on the dataset page: https://huggingface.co/datasets/anton96vice/samantha-1.1-uncensored-split-and-prepared.

Tags

license:apache-2.0size_categories:1K<n<10Kformat:parquetmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:us

README current version from Hugging Face


license: apache-2.0
dataset_info:
features:

  • name: instruction
    dtype: string
  • name: input
    dtype: string
  • name: output
    dtype: string
  • name: text
    dtype: string
    splits:
  • name: train
    num_bytes: 9760644.749754662
    num_examples: 1630
  • name: test
    num_bytes: 2443155.250245339
    num_examples: 408
    download_size: 6418929
    dataset_size: 12203800.0
    configs:
  • config_name: default
    data_files:
    • split: train
      path: data/train-*
    • split: test
      path: data/test-*

Dataset Card for Dataset Name

Samantha-1.1-instructed-uncensored prepared for training

Dataset Details

Dataset Description

This dataset comprises a rich collection of uncensored, instruction-based interactions with Samantha, a virtual assistant designed to perform tasks based on textual commands. Each entry is a detailed record of an instruction provided to Samantha, the input she received, and the output she produced, accompanied by additional textual context. The dataset is intended for use in training and evaluating advanced natural language processing and understanding systems, focusing on interpreting and executing a wide range of instructions accurately.

  • Curated by: Anton Vice
  • Language(s) (NLP): ENGLISH
  • License: Apache

Dataset Sources [optional]

  • Repository: HF

Uses

For training instruction based personal assistant based on movie "Her"

Direct Use

same as any dataset

Out-of-Scope Use

Personal relationships

Dataset Structure

Train and test data with columns:

instruction
User query
AI Response

Dataset Creation

Curation Rationale

reprepare dataset for training personal assistants without the hassle of preparing dataset

Source Data

SOURCE

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. 2024-03-07upd7a6b6562 KB
    Loading...
  2. 2024-03-07Upload dataseta7f14e5524 B
    Loading...
  3. 2024-03-07initial commit981fd8828 B
    Loading...

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 1 thread · 1 open · 1 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. 2024-03-08[bot] Conversion to Parquetopen1 💬#1
    Loading...

Related datasets same stage · fine-tune

Read further

Metadata

License
apache-2.0

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("anton96vice/samantha-1.1-uncensored-split-and-prepared")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="anton96vice/samantha-1.1-uncensored-split-and-prepared", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/anton96vice/samantha-1.1-uncensored-split-and-prepared
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