README.md

metadata

license: apache-2.0
task_categories:
  - text-generation
language:
  - en
tags:
  - agent
  - coding
  - terminal
  - shell
  - pretrain
  - pretraining
  - agentic
  - llm
  - web
  - fineweb
  - dclm
pretty_name: WebTerminal
size_categories:
  - 10M<n<100M

Terminal/CLI Web Text

v0.1

A filtered extract of terminal and command-line content from two large web-text corpora.

Sources

• DCLM (Zyphra/dclm-dedup)
• FineWeb (Salesforce/fineweb_deduplicated)

How it was built

1. Fast filter: skip any document that doesn't contain obvious CLI indicators ($, sudo, pip install, ```bash, root@, etc.)
2. Score: remaining docs are scored (0-34) across five signals, each with a per-match point value and a cap:

Filter	Description	Points	Cap
Prompt patterns	Shell prompts like $ cmd, user@host:~$, >>>, root@, PS C:\	2 per match	10
CLI commands	Known commands: sudo, apt-get, pip install, git clone, docker run, curl, ssh, gcc, etc. (30+ patterns)	1 per unique match	8
stdout patterns	Output indicators: "successfully installed", "cloning into", drwx (ls output), "packets transmitted", "traceback", version strings	2 per match	6
Code blocks	Terminal-flavored code blocks: ```bash, ```shell, <pre><code>, terminal/console div classes	2 per match	6
Indented blocks	3+ consecutive lines indented 4+ spaces (code/output blocks)	1 per match	4

Documents scoring >=5 are kept.

3. Dedup: exact dedup across both datasets using xxhash64 on full text.

Stats

	Chunks	Size	Rows
DCLM	13,144	~229 GB	~18.8M
FineWeb	8,800	~669 GB	~47.5M

Score	Count	%	Cumulative
5	39,025,201	63.62%	63.62%
6	10,787,199	17.59%	81.21%
7	4,063,886	6.63%	87.83%
8	2,911,983	4.75%	92.58%
9	1,304,162	2.13%	94.70%
10	1,022,996	1.67%	96.37%
11-14	1,609,090	2.62%	98.99%
15-20	536,421	0.87%	99.87%
21-34	80,340	0.13%	100.00%
Total	61,341,278

Use case

Mostly for upsampling agentic-adjacent data during pretraining.