dataset

"Specific technical observations (LLM security vulnerabilities, Sora quality, agent readiness) score 88-100% supported with zero contradictions."

"India, home to one of the world's biggest AI user bases, should treat local datasets for AI as a strategic asset to avoid training Silicon Valley for free"

"In this example, we will create a Keras Sequential model and train it on the Cars dataset."

"By utilizing socioculturally-situated, community-engaged methods, including telephonic surveys moderated in native languages, we establish a reproducible methodology that is sensitive to the region's complex linguistic diversity and traditional orality."

"I built SarcasmExplain-5K — a dataset of 5,000 Reddit sarcasm instances, each annotated with 5 types of natural language explanations generated via GPT-4"

"DataClaw README: "Anthropic built their models with freely shared information, then pushed increasingly strict data policies to stop others from doing the same. It's like pulling up the ladder after you've climbed it. DataClaw throws the ladder back.""

"The solution is simple. When receiving a large result set, instead of going through the SQLcl MCP Server, use the SQLcl CLI itself to write to a file directly."

"So we built Klippbok and open sourced it. It's a complete pipeline: scan → triage → caption → extract → validate → organize."

"I'm having trouble training the model so that my accuracy and loss score is good, where the graph sort of plateous."

"I'm trying to fine-tune an MLLM on LLaVA-Instruct dataset (which is a multi-turn chat dataset). I am strugling to build the Dataset and Dataloader classes to train the model, specially because of how to build the labels."

"Hugging Face is an online community for AI that has become the cornerstone for anyone working with AI and machine learning, enabling researchers, developers, and organizations to harness machine learning in ways previously inaccessible."

"down_load_non_qa_rag_data_from_huggingface.py is a Streamlit Web application that obtains, validates, and preprocesses non-Q&A datasets via HuggingFace Hub and direct downloads."

"We introduce MusicRecoIntent, a manually annotated corpus of 2,291 Reddit music requests, labeling musical descriptors across seven categories with positive, negative, or referential preference-bearing roles."

"I just released a dataset I've been working on: a sentence-level corpus extracted from the entire Hebrew Wikipedia."

"I organized the flow of fine-tuning (SFT) a lightweight LLM."

"On this basis, we built an open dataset combining contextual data (demographic data, preferences, visiting habits, motivations, social context. . . ), behavioral data (spatiotemporal trajectories, gaze data) and feedback (satisfaction, fatigue, liked artworks, verbatim. . . )."

"I've added a fresh coat of paint, as well as many new features."

"Took the Epstein Files dataset from Hugging Face (teyler/epstein-files-20k) – 2 million+ pages of trending news and documents."

"Anthropic are the guys that make the Claude Models."

"This problem's core is that the Keras model expects inputs in batches, not single samples."

"We hope the dataset can be used to train LoRA, fine-tune image generation models, and help research in image-edit models."

"So I built an AI copilot that helps you build evals and synthetic datasets. The result: 5x faster development time and 4x lower judge error rates."

"We can happily report that with adapting the model, the word error rate on the selected test data has being reduced to a half, while we managed to remove up to two thirds of the error on character level."

"To address this gap, we introduce WAXAL, a large-scale, openly accessible speech dataset for 21 languages representing over 100 million speakers."

"To bridge this gap, we release EDU-CIRCUIT-HW, a dataset consisting of 1,300+ authentic student handwritten solutions from a university-level STEM course."

"So I just made a dataset that solves that problem."

"By evaluating and ranking the datasets, performing comprehensive analyses, generating fused datasets, conducting external validation, and making our implementation p"

"In this work, we leverage the theory of stochastic Iterated Function Systems (IFS) and show that two important deep architectures can be viewed as, or canonically associated with, place-dependent IFS."

"It can be described as a resource hub, providing a large number of AI datasets, cutting-edge research papers in the field of AI, and daily news updates from the AI ​​community."

"Experiments on the EAGLE framework demonstrate that SFDD can achieve over 2$ imes$ training speedup using only 50% of the data, while keeping the final model's inference speedup within 4% of the full-dataset baseline."