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Most ML projects do not fail because of model choice. They fail in the messy middle: finding the right dataset, checking usability, writing training code, fixing errors, reading logs, debugging weak results, evaluating outputs, and packaging the model for others. This is where ML Intern fits. It is not just AutoML for model selection and […] The post ML Intern in Practice: From Prompt to a Shipped Hugging Face Model appeared first on Analytics Vidhya.
Read full articleParis-based AI real estate startup Davis has raised €4.6 million in a pre-seed round led by Heartcore Capital and Balderton Capital, with participation from Yellow, Evantic, and Entrepreneurs First, alongside angels from the founding teams of Hugging Face, Black Forest Labs, and Supabase. Founded in 2025 by CEO Mehdi Rais and Amine Chraibi, Davis combines […]
In this tutorial, we take a deep dive into the TaskTrove dataset on Hugging Face and build a complete, practical workflow to efficiently explore it. Instead of downloading the full multi-gigabyte dataset, we stream it directly and work with individual samples in real time. We begin by setting up the environment and inspecting the raw […] The post A Coding Implementation to Explore and Analyze the TaskTrove Dataset with Streaming Parsing Visualization and Verifier Detection appeared first on MarkTechPost.
In this tutorial, we explore how to use the ParseBench dataset to evaluate document parsing systems in a structured, practical way. We begin by loading the dataset directly from Hugging Face, inspecting its multiple dimensions, such as text, tables, charts, and layout, and transforming it into a unified dataframe for deeper analysis. As we progress, […] The post A Coding Implementation on Document Parsing Benchmarking with LlamaIndex ParseBench Using Python, Hugging Face, and Evaluation Metrics appeared first on MarkTechPost.
DONOSTIA, Spain, April 28, 2026 — Multiverse Computing today announced the release of the LittleLamb open-source model family, three new ultra-compact models now available for free on Hugging Face. Designed […] The post Multiverse Computing Launches LittleLamb Model Family, Expanding Compact AI for Edge, On-Device, and Agentic Use Cases appeared first on AIwire.
Insider Brief PRESS RELEASE — Multiverse Computing, the leader in AI model compression, today announced the release of the LittleLamb open-source model family, three new ultra-compact models now available for free on Hugging Face. Designed for real-world AI deployment in a smaller footprint, the models are LittleLamb 0.3B, a general-purpose model; LittleLamb 0.3B Tool-Calling, a […]
Hugging Face has released ml-intern, an open-source AI agent designed to automate end-to-end post-training workflows for large language models (LLMs). Built on the company’s smolagents framework, the tool can autonomously perform literature review, dataset discovery, training script execution, and iterative evaluation — tasks that typically require significant manual effort from ML researchers and engineers. What […] The post Hugging Face Releases ml-intern: An Open-Source AI Agent that Automates the LLM Post-Training Workflow appeared first on MarkTechPost.
MiniMax has officially open-sourced MiniMax M2.7, making the model weights publicly available on Hugging Face. Originally announced on March 18, 2026, MiniMax M2.7 is the MiniMax’s most capable open-source model to date — and its first model to actively participate in its own development cycle, a meaningful shift in how large language models are built […] The post MiniMax Just Open Sourced MiniMax M2.7: A Self-Evolving Agent Model that Scores 56.22% on SWE-Pro and 57.0% on Terminal Bench 2 appeared first on MarkTechPost.
