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license: apache-2.0
task_categories:
- text-generation
language:
- en
size_categories:
- 10K<n<100K
---
# Dataset Card for pg19-test
<!-- Provide a quick summary of the dataset. -->
This dataset is a curated subset of the PG-19 dataset (a large collection of classic books from Project Gutenberg), specifically processed to generate text samples with controlled token lengths—using the Llama3.1-8B-Instruct tokenizer for precise tokenization—for long-context language model evaluation and research. The dataset contains stratified text excerpts at six distinct token length targets (10240 to 61440 tokens) with consistent sample sizes per length, ensuring sentence-level coherence (truncation at natural sentence endings) and minimal text reuse.
## Dataset Details
### Key Features
<!-- Provide a longer summary of what this dataset is. -->
- **Length Stratification:** Samples across 6 target token lengths: 10k, 20k, 30k, 40k, 50k, 60k tokens.Note that the actual token length of samples does not strictly adhere to the target values, and a fluctuation of several hundred tokens (either above or below the target) may occur.
- **Coherent Truncation:** Text is truncated at natural sentence endings (.!?) rather than arbitrary token positions to preserve readability and semantic integrity.
- **Language(s) (NLP):** English
- **Size of the dataset:** 54.7MB
### Dataset Sources
<!-- Provide the basic links for the dataset. -->
- **Homepage:** https://huggingface.co/datasets/hcyy/pg19-test
- **Paper:** SpecPV: Improving Self-Speculative Decoding for Long-Context Generation via Partial Verification
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
This dataset consists of 120 text samples structured into two core fields: "length" (an integer representing the target token length, which falls into six tiers: 10k, 20k, 30k, 40k, 50k, 60k tokens) and "text" (a string of coherently truncated PG-19 excerpts ending at natural sentence boundaries); it has 100 samples per length tier, with actual token lengths fluctuating by several hundred tokens around the targets to prioritize coherence, and is available in both Parquet formats.
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
This dataset is used to evaluate the performance of the SpecPV algorithm.
### Source Data
The dataset is directly derived from the PG-19 dataset (hosted at https://huggingface.co/datasets/emozilla/pg19/), a large collection of public-domain books published before 1919 (from Project Gutenberg).
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