license: apache-2.0
thumbnail: "https://i.ibb.co/5M7jWWD/banner.png"
Neural-DPO
Creator: NeuralNovel
Community Organization: ConvexAI
Discord: Join us on Discord
About Neural-DPO: The Neural-DPO dataset, inspired by orca_dpo_pairs contains comprehensive questions and answers with a specific focus on neural networks.
It encompasses a rich array of subjects, drawing from diverse domains such as literature, scientific research, and theoretical inquiries.
This diversity fosters a wide spectrum of applications, including natural language understanding, contextual comprehension, and educational enrichment.
Source Data:
- orca_dpo_pairs (Inspiration)
- Academic Papers Corpus
- Novel Collections
- General Q&A
Phrases Removed:
To enhance the dataset's coherence and relevance across varied contexts, certain phrases have been selectively omitted.
- Couldn't help but
- Can't resist
- I'm sorry, but
- As an AI
- However, it is important to
- Cannot provide
- And others
README history
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.
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Used by abliterated models
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
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.
2024-02-12[bot] Conversion to Parquet
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Download the dataset
0Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.
from datasets import load_dataset
ds = load_dataset("NeuralNovel/Neural-DPO") from huggingface_hub import snapshot_download
snapshot_download(repo_id="NeuralNovel/Neural-DPO", repo_type="dataset") git clone https://huggingface.co/datasets/NeuralNovel/Neural-DPO 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.