Really happy that our (me and Manan Dey) paper has been accepted NeurIPS Conference 2019 Workshop on AI for Social Good". We'll be discussing about the effect of YouTube videos on viewer's mental health. You can read more about our work at thechange.world #AI4Good #NeurIPS

I'll be presenting our poster on assessing viewer's mental health by analysing YouTube videos at AI for Social Good workshop at #NeurIPS2019! Drop by if you’re around! Poster sessions at 9:35-10:30 AM and 3:30-4:15 PM East MR11,12 - with Manan Dey

I'm really happy to share that our work on evaluating gender bias in NLI systems has been accepted at #NeurIPS2020 Workshop on Dataset Curation and Security. Joint work with amazing collaborators Manan Dey and Koustuv Sinha. More details coming soon!

Hi #NeurIPS2020! I and Manan Dey will be presenting our poster on *Evaluating Gender Bias in NLI* at the Workshop on Dataset Curation and Security today (11th Dec) at 2:30 PM EST. Drop by if you're around :) cc: Koustuv Sinha Gather Town (Poster 19) neurips.gather.town/app/A4yaHmXq3U…

First modeling paper out of BigScience is here! T0 shows zero-shot task generalization on English natural language prompts, outperforming GPT-3 on many tasks, while being 16x smaller! Model: huggingface.co/bigscience/T0pp Repo: github.com/bigscience-wor… Paper: arxiv.org/abs/2110.08207

We’ve seen crazy interest in T0++ (pronounced "T Zero Plus Plus"), and almost 10’000 queries to the model since we announced it 3 days ago. Probably the most hilariously decisive prediction from the model (courtesy of Philipp Schmid): 1/N

Tokenization—the least interesting #NLProc topic? Hell no! We, members of the @BigScienceW tokenization group are proud to present: ✨Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP✨ arxiv.org/abs/2112.10508 What's in it? [1/10]

We are releasing PromptSource, a toolkit for creating, sharing, and using natural language prompts. We used it to create the largest open-source collection of English prompts: 2,000 prompts for 170 datasets! 📄 arxiv.org/abs/2202.01279 💻 github.com/bigscience-wor…

🧐🕵️I am looking for the best possible open source tool to do memory profiling! I would like to know what part of my python code is causing these memory usage spikes that don't necessarily come from the Python interpreter. Looking forward to reading your recommendations! 🤗

New paper alert! 🎉 Turns out you can reduce the gender biases your translation models just using relevant contexts, purely during inference! Checkout this cool work led by Shanya Sharma and Manan Dey! arxiv.org/abs/2205.10762 [1/4]

BLOOM is here. The largest open-access multilingual language model ever. Read more about it or get it at bigscience.huggingface.co/blog/bloom hf.co/bigscience/blo…

✨Our work "How sensitive are translation systems to extra contexts? Mitigating gender bias in Neural Machine Translation models through relevant contexts" got accepted at the Findings on EMNLP 2022!✨ Joint work with Manan Dey and our awesome mentor Koustuv Sinha 🎉

Announcing a holiday gift: 🎅SantaCoder - a 1.1B multilingual LM for code that outperforms much larger open-source models on both left-to-right generation and infilling! Demo: hf.co/spaces/bigcode… Paper: hf.co/datasets/bigco… Attribution: hf.co/spaces/bigcode… A🧵:

Introducing: 💫StarCoder StarCoder is a 15B LLM for code with 8k context and trained only on permissive data in 80+ programming languages. It can be prompted to reach 40% pass@1 on HumanEval and act as a Tech Assistant. Try it here: shorturl.at/cYZ06r Release thread🧵

✨New Preprint ✨ How are shifting norms on the web impacting AI? We find: 📉 A rapid decline in the consenting data commons (the web) ⚖️ Differing access to data by company, due to crawling restrictions (e.g.🔻26% OpenAI, 🔻13% Anthropic) ⛔️ Robots.txt preference protocols

✨New Report✨ Our data ecosystem audit across text, speech, and video (✏️,📢,📽️) finds: 📈 Rising reliance on web, synthetic, and YouTube data. 🛑 80%+ datasets carry hidden restrictions. 🌍 Relative representation in languages and creators has not improved for 10+ yrs.

Testing LLMs' reasoning skills is tough—human evaluations are expensive, data contamination is common, and LLM judges can be biased. We propose StructTest, the first benchmark that checks how well LLMs follow complex instructions and create structured outputs. It uses a

Thrilled our global data ecosystem audit was accepted to #ICLR2025! Empirically, we find: 1⃣ Soaring synthetic text data: ~10M tokens (pre-2018) to 100B+ (2024). 2⃣ YouTube is now 70%+ of speech/video data but could block third-party collection. 3⃣ <0.2% of data from