datajuicer/LLaMA-1B-dj-refine-150B
Text Generation
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Updated
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27
Error code: UnexpectedError
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meta
dict | text
string | stats
dict | simhash
float64 |
---|---|---|---|
{} | "Produced by Suzanne Shell, Sjaani and PG Distributed Proofreaders\n\n\n\n\nTHE HOUSE ON THE BORDERL(...TRUNCATED) | {"alnum_ratio":0.7730060037,"avg_line_length":53.1530147895,"char_rep_ratio":0.0357377283,"flagged_w(...TRUNCATED) | 16,879,431,143,088,323,000 |
{} | "This file was produced from images generously made available by the Bibliotheque nationale de Franc(...TRUNCATED) | {"alnum_ratio":0.7912897832,"avg_line_length":59.7947893757,"char_rep_ratio":0.0363826187,"flagged_w(...TRUNCATED) | 3,644,732,410,104,741,400 |
{} | "Produced by Charles Aldarondo, Charlie Kirschner\nand the Online Distributed Proofreading Team.\n\n(...TRUNCATED) | {"alnum_ratio":0.7837232004,"avg_line_length":55.9332659252,"char_rep_ratio":0.0307179452,"flagged_w(...TRUNCATED) | 11,089,683,488,658,866,000 |
{} | "Produced by Christine De Ryck, Stig M. Valstad, Suzanne L. Shell\nand PG Distributed Proofreaders\n(...TRUNCATED) | {"alnum_ratio":0.7885623647,"avg_line_length":58.9589676671,"char_rep_ratio":0.032107734,"flagged_wo(...TRUNCATED) | 6,291,782,967,138,216,000 |
{} | "Produced by Ted Garvin, Dave Morgan and PG Distributed Proofreaders\n\n\n\n\nLA FIAMMETTA\n\nBY\n\n(...TRUNCATED) | {"alnum_ratio":0.7910396996,"avg_line_length":62.9837189374,"char_rep_ratio":0.0197705904,"flagged_w(...TRUNCATED) | 6,492,970,723,819,643,000 |
{} | "Produced by Suzanne Shell, Sjaani and PG Distributed Proofreaders\n\n\n\n\nCARMILLA\n\nJ. Sheridan (...TRUNCATED) | {"alnum_ratio":0.7786372339,"avg_line_length":47.4699603538,"char_rep_ratio":0.0261364001,"flagged_w(...TRUNCATED) | 7,426,944,496,859,436,000 |
{} | "Produced by Suzanne Shell, Danny Wool, Luiz Antonio de Souza,\nElisa Williams, Tonya Allen and PG D(...TRUNCATED) | {"alnum_ratio":0.7687656563,"avg_line_length":43.1778642555,"char_rep_ratio":0.0327301742,"flagged_w(...TRUNCATED) | 14,936,655,909,178,157,000 |
{} | "Produced by Dennis McCarthy\n\n\n\n\n\n\n\n\n\nTHE DIVINE COMEDY\n\nOF DANTE ALIGHIERI\n(1265-1321)(...TRUNCATED) | {"alnum_ratio":0.7484757649,"avg_line_length":32.4585585586,"char_rep_ratio":0.0269562603,"flagged_w(...TRUNCATED) | 16,855,008,483,676,178,000 |
{} | "Produced by Jonathan Ingram and PG Distributed Proofreaders\n\n\n\n\nTHE EULOGIES OF HOWARD.\n\nA V(...TRUNCATED) | {"alnum_ratio":0.8076707115,"avg_line_length":61.8861003861,"char_rep_ratio":0.0252866391,"flagged_w(...TRUNCATED) | 15,541,307,282,155,172,000 |
{} | "Produced by Andrew Heath, Joshua Hutchinson, Audrey Longhurst\nand PG Distributed Proofreaders\n\n\(...TRUNCATED) | {"alnum_ratio":0.7702943221,"avg_line_length":37.780952381,"char_rep_ratio":0.1020916411,"flagged_wo(...TRUNCATED) | 8,229,905,533,405,478,000 |
A refined version of Book dataset in RedPajama by Data-Juicer. Removing some "bad" samples from the original dataset to make it higher-quality.
This dataset is usually used to pretrain a Large Language Model.
Notice: Here is a small subset for previewing. The whole dataset is available here (About 91GB).
# global parameters
project_name: 'Data-Juicer-recipes-book'
dataset_path: '/path/to/your/dataset' # path to your dataset directory or file
export_path: '/path/to/your/dataset.jsonl'
np: 50 # number of subprocess to process your dataset
open_tracer: true
# process schedule
# a list of several process operators with their arguments
process:
- clean_email_mapper:
- clean_links_mapper:
- fix_unicode_mapper:
- punctuation_normalization_mapper:
- whitespace_normalization_mapper:
- alphanumeric_filter:
tokenization: false
min_ratio: 0.55 # <3sigma (0.697)
max_ratio: 0.854 # 3sigma
- average_line_length_filter: # for code
max_len: 500 # >3sigma (364)
- character_repetition_filter:
rep_len: 10
max_ratio: 0.2 # >3sigma (0.12)
- flagged_words_filter:
lang: en
tokenization: true
max_ratio: 0.00047 # 3sigma
- language_id_score_filter: # remove language filter
min_score: 0.2
- maximum_line_length_filter: # for code
max_len: 13381 # 3sigma
- perplexity_filter:
lang: en
max_ppl: 6000 # <3sigma (16516)
- special_characters_filter:
max_ratio: 0.5 # >3sigma (0.32)
- words_num_filter:
lang: en
tokenization: true
min_num: 1000
max_num: 539754 # 3sigma
- word_repetition_filter:
lang: en
tokenization: true
rep_len: 10
max_ratio: 0.194 # 3sigma
- document_simhash_deduplicator:
tokenization: space
window_size: 6
lowercase: true
ignore_pattern: '\p{P}'
num_blocks: 6
hamming_distance: 4