datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
falcon-refinedweb
📀 Falcon RefinedWeb
Falcon RefinedWeb is a massive English web dataset built by TII and released under an ODC-By 1.0 license.
See the 📓 paper on arXiv for more details.
RefinedWeb is built through stringent filtering and large-scale deduplication of CommonCrawl; we found models trained on RefinedWeb to achieve performance in-line or better than models trained on curated datasets, while only relying on web data.
RefinedWeb is also "multimodal-friendly": it contains links and… See the full description on the dataset page: https://huggingface.co/datasets/tiiuae/falcon-refinedweb.falcon-refinedweb
📀 Falcon RefinedWeb
Falcon RefinedWeb is a massive English web dataset built by TII and released under an ODC-By 1.0 license.
See the 📓 paper on arXiv for more details.
RefinedWeb is built through stringent filtering and large-scale deduplication of CommonCrawl; we found models trained on RefinedWeb to achieve performance in-line or better than models trained on curated datasets, while only relying on web data.
RefinedWeb is also "multimodal-friendly": it contains links and… See the full description on the dataset page: https://huggingface.co/datasets/Velcry/falcon-refinedweb.falcon-refinedweb_urls
Dataset Card for falcon-refinedweb_urls
This dataset provides the URLs and top-level domains associated with training records in tiiuae/falcon-refinedweb. It is part of a collection of datasets curated to make exploring LLM training datasets more straightforward and accessible.
Dataset Details
Dataset Description
This dataset was created by downloading the source data, extracting URLs and top-level domains, and retaining only those record identifiers.… See the full description on the dataset page: https://huggingface.co/datasets/nhagar/falcon-refinedweb_urls.falcon-refinedweb
📀 Falcon RefinedWeb
Falcon RefinedWeb is a massive English web dataset built by TII and released under an ODC-By 1.0 license.
See the 📓 paper on arXiv for more details.
RefinedWeb is built through stringent filtering and large-scale deduplication of CommonCrawl; we found models trained on RefinedWeb to achieve performance in-line or better than models trained on curated datasets, while only relying on web data.
RefinedWeb is also "multimodal-friendly": it contains links and… See the full description on the dataset page: https://huggingface.co/datasets/tmtanu/falcon-refinedweb.ptb_text_onlyThis is the Penn Treebank Project: Release 2 CDROM, featuring a million words of 1989 Wall Street Journal material. This corpus has been annotated for part-of-speech (POS) information. In addition, over half of it has been annotated for skeletal syntactic structure.falcon-refinedweb-1B
Falcon RefinedWeb 1B
Dataset Description
This is a 1.01 Billion token subset of the tiiuae/falcon-refinedweb dataset. It was created by streaming the dataset with a large shuffle buffer to ensure a random, representative sample of the web data.
Motivation
RefinedWeb is a high-quality filtered web dataset, but the full version is massive. This 1B token slice provides a perfect testbed for evaluating model architecture changes or for use in curriculum learning… See the full description on the dataset page: https://huggingface.co/datasets/krisbailey/falcon-refinedweb-1B.BlockData-minecraft-10k
Dataset Card for Dataset Name
Minecraft dataset features user-AI interactions, providing gameplay advice and strategies.
Dataset Details
Dataset Description
The Minecraft dataset on Hugging Face consists of 6,390 rows of interactions between users and an AI assistant designed to provide expert advice on Minecraft. It includes questions about gameplay strategies, such as efficient storage options, diamond farming tips, and mining improvements. The assistant… See the full description on the dataset page: https://huggingface.co/datasets/FalconNet/BlockData-minecraft-10k.falcon_code
FalconCode
FalconCode is a large-scale dataset of student programming solutions, collected from multiple introductory programming courses.It is designed for research on automatic programming feedback, code understanding, and educational AI.The dataset has been curated and processed for SIGCSE 2024 and is described in detail in the FalconCode project page.
Access Requests
Please use your institutional email addresses when submitting an access request.
You should… See the full description on the dataset page: https://huggingface.co/datasets/koutch/falcon_code.query-parsing-instructions-falcon
Synthetic Search Query Parsing Instruction for Instruct Falcon family
This is the version of EmbeddingStudio/synthetic-search-queries dataset created the way to be aligned with Falcon-7B-Instruct instruction format.
Generation details
We used synthetically generated query parsing instructions:
We generated lists of possible filters for 63 customer categories:
Raw version of filters dataset
Split by representations
Select randomly up-to 150 possible combinations (1-3… See the full description on the dataset page: https://huggingface.co/datasets/EmbeddingStudio/query-parsing-instructions-falcon.falcon-refinedweb-1M_en_medium
BEE-spoke-data/falcon-refinedweb-1M_en_medium
A sample from falcon-refinedweb:
more than 512 & less than 8192 gpt4 tiktoken tokens
en only (via fasttext-langdetect)
1M samples
GPT-4 tiktoken token count:
token_count
count 1000000.000000
mean 1197.179246
std 964.177338
min 513.000000
25% 653.000000
50% 871.000000
75% 1315.000000
max 8191.000000
Total count: 1197.18 M tokens
falcon-snort-cti-rule
FALCON SNORT CTI ↔ Ground-Truth Rule Dataset
Cyber-threat-intelligence descriptions paired with their ground-truth SNORT IDS rule and the LLM-generated decoy rules (hard-negative look-alikes) of that gold rule. This is the FALCON held-out test benchmark used both for LLM rule-generation evaluation and for retrieval testing of contrastively fine-tuned sentence encoders.
Schema
column
type
description
cti
string
CTI description
gold_rule
string… See the full description on the dataset page: https://huggingface.co/datasets/shaswatamitra/falcon-snort-cti-rule.falcon-yara-cti-rule
FALCON YARA CTI ↔ Ground-Truth Rule Dataset
Cyber-threat-intelligence descriptions paired with their ground-truth YARA rule and the LLM-generated decoy rules (hard-negative look-alikes) of that gold rule. This is the FALCON held-out test benchmark used both for LLM rule-generation evaluation and for retrieval testing of contrastively fine-tuned sentence encoders.
Schema
column
type
description
cti
string
CTI description
gold_rule
string
ground-truth… See the full description on the dataset page: https://huggingface.co/datasets/shaswatamitra/falcon-yara-cti-rule.falcon-refinedweb-100k_en-long
BEE-spoke-data/falcon-refinedweb-100k_en-long
A sample from falcon-refinedweb:
more than 2048 & less than 16384 gpt4 tiktoken tokens
en only (via fasttext-langdetect)
100k samples
Synthetic-NoRobots
Syntetic NoRobots: How is this possible?
-- All user's prompts were generated by LLama-70b-Nemotron
-- All AI's outputs were grabbed from Fineweb-2 Dataset
It took only 0.2$ to create!
Here's a code used for creating this:
import requests
import json
from datasets import load_dataset, Dataset
import random
from tqdm import tqdm
import time
import concurrent.futures
import threading
import re
API_KEY = "..." # Openrouter
print("###… See the full description on the dataset page: https://huggingface.co/datasets/FalconNet/Synthetic-NoRobots.falcon-refinedweb-100k_en-xlong
BEE-spoke-data/falcon-refinedweb-100k_en-xlong
A sample from falcon-refinedweb:
more than 4096 & less than 34,000 gpt4 tiktoken tokens
en only (via fasttext-langdetect)
100k samples
falcon-refinedweb-100k_en_med-sample
BEE-spoke-data/falcon-refinedweb-100k_en_med-sample
A sample from falcon-refinedweb:
more than 512 & less than 8192 llama2 tokens
en only (via fasttext-langdetect)
100k samples
falcon-refinedweb-100M
falcon-refinedweb-100M
Dataset Description
This is a 100.0 Million token subset of krisbailey/falcon-refinedweb-1B, which is a subset of tiiuae/falcon-refinedweb.
Motivation
100M tokens is a standard size for:
CI/CD Pipelines: Fast enough to download and train for unit tests.
Debugging: Verifying training loops without waiting for hours.
Scaling Laws: The first step in a logarithmic scaling series (100M -> 1B -> 10B).
Dataset Details
Total Tokens:… See the full description on the dataset page: https://huggingface.co/datasets/krisbailey/falcon-refinedweb-100M.fatimah-falcon3-3b-base-blindspots
Falcon3-3B-Base — Blind Spot Evaluation Dataset
This dataset documents 10 confirmed, diverse failure modes ("blind spots") of
tiiuae/Falcon3-3B-Base, a raw
pretrained 3B causal language model released by the Technology Innovation Institute
in December 2024. Every data point was empirically verified — the model was run live
and confirmed to produce the wrong output before inclusion.
Model Under Test
Field
Value
Model
tiiuae/Falcon3-3B-Base
Size
3B… See the full description on the dataset page: https://huggingface.co/datasets/Abdulsobur/fatimah-falcon3-3b-base-blindspots.FalconDataset