datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
proof-pile-2-streaming
ArXiv | Models | Data | Code | Blog | Sample Explorer
Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, Marco Dos Santos, Stephen McAleer, Albert Q. Jiang, Jia Deng, Stella Biderman, Sean Welleck
The Proof-Pile-2 is a 55 billion token dataset of mathematical and scientific documents. This dataset was created in order to train the Llemma 7B and Llemma 34B models. It consists of three subsets:
arxiv (29B tokens): the ArXiv subset of RedPajama
open-web-math (15B tokens): The OpenWebMath… See the full description on the dataset page: https://huggingface.co/datasets/xavierdurawa/proof-pile-2-streaming.omnimcp_data_kafka_streaming_teaser
🔬 INSPECT THE DEEPSEEK-R1 REASONING CHAIN LIVE:
Zero hallucinations. Null syntax errors. 100% AST compiler validated.🌐 Live Interactive Reasoning & Code Inspector: https://emgena.com/trainingslager🎁 Claim your Free Starter Kit (Code: STARTER100): https://emgena.com/trainingslager🏷️ Launch Discount: Get 20 € OFF any 500-incident production suite with code LAUNCH20!
📜 Enterprise Compliance: EU AI Act Articles 50 & 53 certified • 100% DSGVO / GDPR clean • Commercial EULA… See the full description on the dataset page: https://huggingface.co/datasets/emgena/omnimcp_data_kafka_streaming_teaser.smollm-corpus-instruct-2M-cosmopedia-v2-gpt2-v2-streaming
A corpus of high quality fine tuning data meant for fine tuning various HelixLM models
Dataset Composition:
A subset sampled from randomly selected shards from https://huggingface.co/datasets/HuggingFaceTB/smollm-corpus cosmopedia-v2 split ...
Added: A preprocessed column formattedconversation concatenating the prompt, text and special tokens for instruct fine tuning.
Added: A token count column tokencount based on GPT2 tokenizer + the fine tuning special tokens.… See the full description on the dataset page: https://huggingface.co/datasets/david-thrower/smollm-corpus-instruct-2M-cosmopedia-v2-gpt2-v2-streaming.live-streaming-content
直播内容训练数据集
数据集简介
这个数据集包含直播记录的对话训练数据，适用于：
微调语言模型以生成直播风格的内容
构建直播内容问答系统
RAG (检索增强生成) 系统训练
数据格式
1. SFT 格式 (training_sft.jsonl)
对话式训练数据，适用于监督微调：
{
"messages": [
{"role": "system", "content": "你是一个专业的直播内容助手..."},
{"role": "user", "content": "请介绍一下..."},
{"role": "assistant", "content": "..."}
]
}
2. RAG 格式 (training_rag.jsonl)
问答对格式，包含上下文：
{
"question": "...",
"context": "...",
"answer": "...",
"metadata": {...}
}… See the full description on the dataset page: https://huggingface.co/datasets/licco123/live-streaming-content.StreamingCoT
Streaming Reasoning Math Train/Eval
This dataset is built for streaming real-time reasoning. It provides math
reasoning examples where a model should reason while the input is being read,
rather than waiting for the complete problem context before starting to think.
The dataset is organized into two Hugging Face configs:
Train: supervised fine-tuning data for learning streaming reasoning traces.
Eval: held-out evaluation data with three benchmark splits.
The training reasoning… See the full description on the dataset page: https://huggingface.co/datasets/JunlongTong/StreamingCoT.openclaw-streaming-alert
openclaw-streaming-alert - Sound notification for OpenClaw Web UI - chime on completion, alert on stall.
Mirrored in two places, same version everywhere:
Hugging Face (you are here) · GitLab
Get the files - GitLab is the most reliable plain-git route:
git clone https://gitlab.com/LucioLiu/openclaw-streaming-alert.git
# or from this page
hf download LucioLiu/openclaw-streaming-alert --repo-type dataset --local-dir ./openclaw-streaming-alert
Licence: MIT
🔔 OpenClaw Streaming… See the full description on the dataset page: https://huggingface.co/datasets/LucioLiu/openclaw-streaming-alert.streaming-tokenizer-shard-writer
streaming-tokenizer-shard-writer (sample shards)
Sample output from the streaming-tokenizer-shard-writer
pipeline: a streaming, parallel tokenizer that packs a text corpus into
fixed-size, size-balanced training shards using bounded memory.
What is here
shard-000000.tar, shard-000001.tar — two sample shards. Each is a
dependency-free tar archive (webdataset-style); every member is one tokenized
sample named <shard>-<seq>.ids, whose payload is the token ids packed… See the full description on the dataset page: https://huggingface.co/datasets/narinzar/streaming-tokenizer-shard-writer.