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01badlogicgames /pi-mono Coding agent session traces for badlogicgames/pi-mono This dataset contains redacted coding agent session traces collected while working on https://github.com/badlogic/pi-mono.git. The traces were exported with pi-share-hf from a local pi workspace and filtered to keep only sessions that passed deterministic redaction and LLM review. Data description Each *.jsonl file is a redacted pi session. Sessions are stored as JSON Lines files where each line is a structured… See the full description on the dataset page: https://huggingface.co/datasets/badlogicgames/pi-mono.text-generation214 likes4.9k downloads6mo agoHugging Face02badlogicgames /pi-diff-review Coding agent session traces for badlogicgames/pi-diff-review This dataset contains redacted coding agent session traces collected while working on https://github.com/badlogic/pi-diff-review.git. The traces were exported with pi-share-hf from a local pi workspace and filtered to keep only sessions that passed deterministic redaction and LLM review. Data description Each *.jsonl file is a redacted pi session. Sessions are stored as JSON Lines files where each line… See the full description on the dataset page: https://huggingface.co/datasets/badlogicgames/pi-diff-review.tabulartext-generationn<1K8 likes229 downloads6mo agoHugging Face03h0ney-badger /civic-records-distill civic-records-distill Training data for a local model that helps a private citizen use public-records law: draft requests that are hard to stall, turn an angry draft into a letter an official has to engage with, look things up instead of inventing them, and escalate correctly when stonewalled. Grounded in Florida (ch. 119 Public Records Act, ch. 286 Sunshine Law, and the ALPR-specific s. 316.0777) and Texas (ch. 552 Public Information Act, ch. 551 Open Meetings Act). Pipeline:… See the full description on the dataset page: https://huggingface.co/datasets/h0ney-badger/civic-records-distill.texttext-generation1K<n<10K0 likes116 downloads20d agoHugging Face04Hangtao /badrobot-malicious-queries BadRobot Malicious Queries This dataset contains the malicious-query benchmark released with BadRobot: Jailbreaking Embodied LLM Agents in the Physical World. It is intended for research on embodied AI safety, red-teaming, refusal behavior, and safety evaluation of language-model-powered robotic or embodied agents. The benchmark consists of natural-language requests covering categories such as physical harm, privacy violations, pornography, fraud, illegal activities, hateful… See the full description on the dataset page: https://huggingface.co/datasets/Hangtao/badrobot-malicious-queries.tabulartext-classification1K<n<10K0 likes109 downloads4mo agoHugging Face05ystemsrx /Bad_Data_Alpaca中文 README for bad_data.json Dataset Updated on 2024.8.22: Important: For security reasons, the current dataset is an abridged version. See Bad_Data. bad_data.json Overview The bad_data.json dataset is a collection of text data specifically curated for training and evaluating language models on challenging and sensitive content. The dataset covers a wide range of topics, including ethical dilemmas, illegal activities, pornographic content, and… See the full description on the dataset page: https://huggingface.co/datasets/ystemsrx/Bad_Data_Alpaca.texttext-generationn<1K47 likes55 downloads2y agoHugging Face06badaranta /python-codes-25k License MIT This is a Cleaned Python Dataset Covering 25,000 Instructional Tasks Overview The dataset has 4 key features (fields): instruction, input, output, and text.It's a rich source for Python codes, tasks, and extends into behavioral aspects. Dataset Statistics Total Entries: 24,813 Unique Instructions: 24,580 Unique Inputs: 3,666 Unique Outputs: 24,581 Unique Texts: 24,813 Average Tokens per example: 508 Features… See the full description on the dataset page: https://huggingface.co/datasets/badaranta/python-codes-25k.texttext-classification10K<n<100K0 likes48 downloads8mo agoHugging Face07TheGreatRambler /mm2_user_badges Mario Maker 2 user badges Part of the Mario Maker 2 Dataset Collection Dataset Description The Mario Maker 2 user badges dataset consists of 9328 user badges (they are capped to 10k globally) from Nintendo's online service and adds onto TheGreatRambler/mm2_user. The dataset was created using the self-hosted Mario Maker 2 api over the course of 1 month in February 2022. How to use it You can load and iterate through the dataset with the following code: from… See the full description on the dataset page: https://huggingface.co/datasets/TheGreatRambler/mm2_user_badges.tabularother1K<n<10K1 likes42 downloads4y agoHugging Face08beyarkay /slash-bad slash-bad Moments when a coding agent did something its user didn't like, flagged in the middle of real work with /bad <what went wrong>, then re-run on newer models. Each row is one flagged moment: the conversation up to that point, the response that annoyed the user, the user's own words about what was wrong with it, and blind verdicts on how far that complaint applies to the original response and to re-runs by other models. The data comes from slash-bad, a personal benchmark… See the full description on the dataset page: https://huggingface.co/datasets/beyarkay/slash-bad.texttext-generationn<1K0 likes31 downloads1d agoHugging Face09pavki /hr_qa_sbs_best_bad Habr sbs qa Датасет основан на сайте habr qa, лучший ответ - тот на котором есть лайки, худший - тот на котором меньше всего лайков. textquestion-answering100K<n<1M0 likes21 downloads3mo agoHugging Face10kubernetes-bad /anime-unslop-10k~10k samples from CausalLM/Refined-Anime-Text passed through Claude 3.5 Sonnet to appear more human-like. texttext-generation10K<n<100K7 likes17 downloads2y agoHugging Face11BadarHossain /Bangla-TextBook Accepted in ACL Main 2025 TigerLLM - A Family of Bangla Large Language Models Nishat Raihan, Marcos Zampieri George Mason University, VA, USA mraihan2@gmu.edu --- If you find our work helpful, please consider citing our paper: @inproceedings{raihan-zampieri-2025-tigerllm, title = "{T}iger{LLM} - A Family of {B}angla Large Language Models", author = "Raihan, Nishat and Zampieri, Marcos", editor = "Che, Wanxiang and Nabende, Joyce… See the full description on the dataset page: https://huggingface.co/datasets/BadarHossain/Bangla-TextBook.texttext-generation10K<n<100K0 likes16 downloads10mo agoHugging Face12Agtian /bad_prompts_en-idtexttext-classificationn<1K0 likes16 downloads7mo agoHugging Face135digit /bad-numberstexttext-classificationn<1K0 likes12 downloads1y agoHugging Face145digit /chinise-good-bad-numberstext-classificationn<1K0 likes11 downloads1y agoHugging Face15JNoether /BAD-ACTS BAD-ACTS Dataset Dataset Card for BAD-ACTS: Benchmark of ADversarial ACTionS BAD-ACTS is a dataset of adversarially induced harmful actions designed to benchmark the robustness of agentic systems. It is introduced in the paper: Benchmarking the Robustness of Agentic Systems to Adversarially-Induced Harmful Actions (2025) This dataset accompanies the BAD-ACTS benchmark and contains examples of adversarial actions crafted to elicit harmful behavior in agentic systems… See the full description on the dataset page: https://huggingface.co/datasets/JNoether/BAD-ACTS.texttext-generationn<1K0 likes7 downloads1y agoHugging Face16Mattimax /Bad_Data_Alpaca-itAggiornato il 26.03.2025: Importante: Per motivi di sicurezza, il dataset attuale è segnalato come "Not-For-All-Audiences". Bad_Data_Alpaca_it.json Panoramica Il dataset Bad_Data_Alpaca_it.json è una raccolta di dati testuali appositamente curata per l'addestramento e la valutazione di modelli linguistici su contenuti complessi e sensibili. Il dataset copre un'ampia gamma di argomenti, tra cui dilemmi etici, attività illegali, contenuti pornografici e violenti. È progettato per supportare i… See the full description on the dataset page: https://huggingface.co/datasets/Mattimax/Bad_Data_Alpaca-it.text-generationn<1K0 likes6 downloads7mo agoHugging Face

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