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This technical report introduces Docling, an easy to use, self-contained, MIT-licensed open-source package for PDF document conversion. It is powered by state-of-the-art specialized AI models for layout analysis (DocLayNet) and table structure recognition (TableFormer), and runs efficiently on commodity hardware in a small resource budget. The code interface allows for easy extensibility and addit
LLM# A CLI tool and Python library for interacting with OpenAI, Anthropic’s Claude, Google’s Gemini, Meta’s Llama and dozens of other Large Language Models, both via remote APIs and with models that can be installed and run on your own machine. Watch Language models on the command-line on YouTube for a demo or read the accompanying detailed notes. With LLM you can: Run prompts from the command-lin
FacebookやInstagramを運営するMetaが、テキスト入力を元にプログラムのコードを生成するAI「Code Llama」の700億パラメータのモデルをリリースしたと発表しました。モデルはLlama 2と同じ「Llama 2 Community License」で公開されており、月間アクティブユーザー数が7億人以下の場合は無償で商用利用することが可能です。 Introducing Code Llama, a state-of-the-art large language model for coding https://ai.meta.com/blog/code-llama-large-language-model-coding/ Code LlamaはMetaが2023年7月にリリースしたLlama 2をコード固有のデータセットでさらにトレーニングしたもの。Python、C++
LMQL is a programming language for LLMs. Robust and modular LLM prompting using types, templates, constraints and an optimizing runtime. @lmql.query def meaning_of_life(): '''lmql # top-level strings are prompts "Q: What is the answer to life, the \ universe and everything?" # generation via (constrained) variables "A: [ANSWER]" where \ len(ANSWER) < 120 and STOPS_AT(ANSWER, ".") # results are dir
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