Show HN: A lightweight RAG evaluator with golden-set metrics
Article URL: https://github.com/infrixo-systems/rag-evaluation-starter Comments URL: https://news.ycombinator.com/item?id=50422943 Points: 1 # Comments: 0
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Show HN: Nino – Fastest C# serializer, safe on untrusted input, also TS/Go/Rust
Nino is a source-generated binary serializer for C#, and as far as we know the fastest one. In the same BenchmarkDotNet run on GitHub runners against MemoryPack 1.21.4, it serializes classes and polymorphic types 3.5–7.2x faster and deserializes them 1.7–2.1x faster (arrays of unmanaged structs are on par). Deserializing into existing objects allocates nothing. Reproduce: https://nino.xgamedev.net/en/docs/v4/benchmarksIt is built to read bytes you do not trust: lengths are checked before allocating, depth is bounded, hash flooding is limited, and the read paths are fuzzed in CI.The bytes are a spec, not a memory dump, so CoreCLR, Mono, IL2CPP and 32-bit hosts write the same bytes, and runtimes for TypeScript, Go and Rust pass the same conformance corpus.Trade-offs: positional by default (VersionTolerant or Keyed for stored data), a 4-byte type id on polymorphic values, no System.Type, needs C# 9 and Roslyn 4.3+.Docs: https://nino.xgamedev.net Comments URL: https://news.ycombinator.com/item?id=50413601 Points: 1 # Comments: 0
SageMaker Inference now supports Multi-Instance GPU to maximize GPU utilization for model endpoints
Amazon SageMaker Inference now supports GPU partitioning with NVIDIA Multi-Instance GPU (MIG), which divides one GPU into hardware-isolated partitions so you can run a different model in each or take a right-sized fraction of a newer accelerator. This post shows how two optional API fields place one model per partition, and what we measured against a whole older GPU.
Show HN: Combining Bursts of Images
An approach of taking many photos to enhance one final image is a technique called "stacking". Stacking alone doesn't account for everything so this is a take that helps get better alignment of images, allows comparisons, and drop bad images that dont match. Its not super resolution but it feels like when you look at it. it reduces the noise and makes it look more organic shot with less expensive hardware. enjoy! Comments URL: https://news.ycombinator.com/item?id=50401218 Points: 1 # Comments: 0
Generate incredible images with Google's Imagen 4
Google's flagship image generation model, Imagen 4, is now available for you to try on Replicate. Create images with fine detail, versatile styles, and improved typography.
Qwen2.5-1M: Deploy Your Own Qwen with Context Length up to 1M Tokens
Tech Report HuggingFace ModelScope Qwen Chat HuggingFace Demo ModelScope Demo DISCORD Introduction Two months after upgrading Qwen2.5-Turbo to support context length up to one million tokens, we are back with the open-source Qwen2.5-1M models and the corresponding inference framework support. Here’s what you can expect from this release: Opensource Models: We’re releasing two new checkpoints, Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M, marking the first time we’ve upgraded our opensource Qwen models to handle 1M-token contexts.
OFA: Towards Building a One-For-All Model
2022 is a year of generalist models! With the bloom of multimodal pretraining, especially the unified model, we have witnessed the opportunity to building a generalist model that is capable of processing tasks of different modalities or multi-modalities! Thus, we propose OFA1, namely One-For-All, a unified multimodal pretrained model that unifies understanding and generation tasks concerning modalities into a single framework, and we pretrain OFA with the instruction-based multitask-pretraining that endows it with multiple capabilities.