ollaya
Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe-compatible API. Ollama for decision models.
https://github.com/ollaya-dev/ollaya
Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe-compatible API. Ollama for decision models.
https://github.com/ollaya-dev/ollaya
GitHub
GitHub - ollaya-dev/ollaya: Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe…
Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe-compatible API. Ollama for decision models. - ollaya-dev/ollaya
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Language Models for Text Classification: From Bag-of-Words to Jev
A concise history of text classification, from bag-of-words and neural networks to transformers and modern LLM-based approaches. It also introduces Jev and examines where specialized classifiers can still outperform or complement general-purpose language models.
https://magazine.sebastianraschka.com/p/classifier-history-and-jev
A concise history of text classification, from bag-of-words and neural networks to transformers and modern LLM-based approaches. It also introduces Jev and examines where specialized classifiers can still outperform or complement general-purpose language models.
https://magazine.sebastianraschka.com/p/classifier-history-and-jev
Sebastian Raschka, PhD
Language Models for Text Classification: From Bag-of-Words to Jev
A Visual Guide to RNNs, CNNs, Transformers, and Calibration, with Hands-On Experiments on Accuracy and Efficiency
Building an Ultra-High Throughput AI-SQL Engine
Quail is an open-source AI-SQL engine that jointly optimizes query planning and LLM inference to reduce redundant model work and keep GPUs busy when running large numbers of AI-powered database operations. In benchmarks across 29 queries, it was 1.84x faster on average than tuned vLLM baselines and up to 14.04x faster on a workload with substantial KV-cache reuse.
https://fsdatalab.github.io/blog/introducing-quail/
Quail is an open-source AI-SQL engine that jointly optimizes query planning and LLM inference to reduce redundant model work and keep GPUs busy when running large numbers of AI-powered database operations. In benchmarks across 29 queries, it was 1.84x faster on average than tuned vLLM baselines and up to 14.04x faster on a workload with substantial KV-cache reuse.
https://fsdatalab.github.io/blog/introducing-quail/
Full Stack Data Lab
Building an Ultra-High Throughput AI-SQL Engine
Quail jointly plans AI-SQL queries and model inference. Across 29 QUAIL-B queries, it is 1.84x faster on average than well-tuned vLLM baselines.