gss1147/high_priest_gnosticism_100k

---

language:

• en license:
• other tags:
• gnosticism
• high-priest
• religious-texts
• theology
• nag-hammadi
• pistis-sophia
• spiritual
• philosophical size_categories:
• 100K<n<1M

"Gnostic High Priest Dataset"

Gnostic High Priest Dataset (100k)

Dataset Description

This dataset contains 100,000 unique instruction-response pairs designed to train language models to reason and think from the perspective of a Gnostic high priest. The dataset is constructed from authentic Gnostic texts including the Nag Hammadi Library, Pistis Sophia, Gospel of Thomas, and other ancient Gnostic scriptures.

Dataset Summary

• Total Examples: 100,000
• File Format: JSONL (JSON Lines)
• File Size: ~73 MB
• Duplicates: 0 (verified unique)
• Languages: English (with some archaic theological terminology)

Supported Tasks

• Instruction Tuning / Supervised Fine-Tuning (SFT)
• Teaching LLMs to adopt a Gnostic high priest persona
• Training models to reason about Gnostic theology, cosmology, and spirituality
• Developing context-aware religious/philosophical dialogue systems

Dataset Structure

Data Fields

Each example contains the following fields:

Field	Type	Description
instruction	string	The question, task, or prompt for the model
response	string	The expected response from a Gnostic high priest perspective
type	string	Category of the example (see below)
source	string	Original Gnostic text source

Type Distribution

Type	Count	Percentage	Description
priest_reflection	23,033	23.0%	High priest reflecting on Gnostic passages
practical_guidance	23,024	23.0%	Guidance for spiritual seekers from priest perspective
direct_teaching	22,834	22.8%	Direct teachings from Gnostic texts
theological_analysis	20,148	20.1%	Analysis of theological implications
concept_explanation	10,961	11.0%	Explanation of Gnostic concepts and terms

Data Splits

Recommended split:

• Train: 90,000 examples (90%)
• Validation: 5,000 examples (5%)
• Test: 5,000 examples (5%)

from datasets import load_dataset

dataset = load_dataset('json', data_files='high_priest_gnosticism_100k.jsonl')
dataset = dataset['train'].train_test_split(test_size=0.1, seed=42)
temp = dataset['test'].train_test_split(test_size=0.5, seed=42)
dataset = {
    'train': dataset['train'],
    'validation': temp['train'],
    'test': temp['test']
}

Dataset Creation

Source Data

Extracted from 22 authentic Gnostic texts:

Source	Examples	Percentage
the_gnostic_bible	32,320	32.3%
The Nag Hammadi Library - James M. Robinson	25,511	25.5%
pistis sophia_complete_text	13,458	13.5%
The_Gospels_of_Thomas	9,862	9.9%
Gospel-of-Philip	7,480	7.5%
BOOKS OF JEU_UNTITLED TEXT BRUCE CODEX_text	~5,600	5.6%
Other Nag Hammadi texts	~5,769	5.7%

Text Extraction and Processing

1. PDF Extraction: Used PyMuPDF (fitz) to extract text from 22 PDF files
2. Cleaning: Removed OCR artifacts, page numbers, headers/footers, and corrupted characters
3. Chunking: Split texts into coherent chunks (200-600 characters)
4. Example Generation: Created 5 types of instruction-response pairs per chunk
5. Deduplication: MD5 hashing ensured zero duplicates
6. Augmentation: Generated variations of instructions to reach 100k examples

Quality Control

• Uniqueness: Verified 0 duplicates via hash checking
• OCR Artifacts: 0 examples with excessive numbers/corrupted text
• Response Length: Min 201, Max 805, Average 485 characters
• Non-ASCII: Only 29 examples with special characters (intentional archaic terms)

Considerations for Use

Recommended Use Cases

• Fine-tuning LLMs for religious/philosophical dialogue
• Training models to understand Gnostic thought and terminology
• Creating spiritual guidance chatbots with Gnostic perspective
• Academic research on religious NLP

Limitations

• Responses are based on specific Gnostic texts and may not represent all Gnostic traditions
• Some examples contain archaic language and theological complexity
• The "high priest" persona is a constructed interpretation, not an authentic historical voice
• Dataset is English-only; original texts may have been translated from Coptic, Greek, etc.

Ethical Considerations

• This dataset represents specific religious viewpoints and should be used respectfully
• Not intended to replace authentic spiritual guidance or religious authority
• Users should be aware that Gnostic teachings may conflict with other religious traditions
• Models trained on this dataset should disclose their training data and perspective

Bias and Fairness

• Dataset focuses exclusively on Gnostic Christianity and related traditions
• Does not represent mainstream Christian, Jewish, Islamic, or other religious perspectives
• The "high priest" framing is a specific interpretive lens

Citation

If you use this dataset, please cite:

@dataset{gnostic_high_priest_2026,
  author = {Generated for Gnostic High Priest Training},
  title = {Gnostic High Priest Dataset: 100k Instruction-Response Pairs for Training LLMs},
  year = {2026},
  howpublished = {\url{https://huggingface.co/datasets/[your-username]/gnostic-high-priest-100k}},
  note = {Dataset generated from authentic Gnostic texts including Nag Hammadi Library, Pistis Sophia, and other ancient sources}
}

Dataset Card Contact

For questions or issues regarding this dataset, please open an issue on the Hugging Face dataset repository.

---

Sample Data

Example 1 (priest_reflection):

{
  "instruction": "As a high priest of the Gnostic tradition, interpret this passage from 'the_gnostic_bible':\n Adam and Eve, through Seth...",
  "response": "From the sacred wisdom of the high priesthood, I contemplate this mystery: Adam and Eve were the first parents, through whom the divine light is communicated to enlightened gnostics... This reveals the path of gnosis - the divine spark within must awaken to transcend the archonic powers.",
  "type": "priest_reflection",
  "source": "the_gnostic_bible"
}

Example 2 (direct_teaching):

{
  "instruction": "Based on the Gnostic text 'Gospel-of-Philip', explain the following teaching:\n It is probably adventurous to suggest that Philip here preserves an echo...",
  "response": "It is probably adventurous to suggest that Philip here preserves an echo of Israelite reaction against the innovation, but whatever its history and antecedents the passage clearly rejects sacrifice...",
  "type": "direct_teaching",
  "source": "Gospel-of-Philip"
}

Loading the Dataset

from datasets import load_dataset

# Load from local file
dataset = load_dataset('json', data_files='high_priest_gnosticism_100k.jsonl')

# Or after uploading to Hugging Face
dataset = load_dataset('your-username/gnostic-high-priest-100k')

Training Example (with transformers)

from transformers import AutoTokenizer, AutoModelForCausalLM
from datasets import load_dataset

# Load dataset
dataset = load_dataset('json', data_files='high_priest_gnosticism_100k.jsonl')

# Format for training
def format_instruction(example):
    return {
        "text": f"### Instruction:\n{example['instruction']}\n\n### Response:\n{example['response']}"
    }

dataset = dataset.map(format_instruction)