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- Structured decoding in LLMs, a guide for the impatient https://aarnphm.xyz/posts/structured-decoding 0 comments
Linked pages
- [1712.01815] Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm https://arxiv.org/abs/1712.01815 573 comments
- [1706.03762] Attention Is All You Need https://arxiv.org/abs/1706.03762 145 comments
- LLM Visualization https://bbycroft.net/llm 139 comments
- Nietzsche and the Significance of Genealogy | Mind | Oxford Academic https://doi.org/10.1093/mind/LIX.236.433 7 comments
- Bevor Sie zu YouTube weitergehen https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi 4 comments
- GitHub - mlc-ai/xgrammar: Efficient, Flexible and Portable Structured Generation https://github.com/mlc-ai/xgrammar 1 comment
- [2001.08361] Scaling Laws for Neural Language Models https://arxiv.org/abs/2001.08361 0 comments
- [1301.3781] Efficient Estimation of Word Representations in Vector Space https://arxiv.org/abs/1301.3781 0 comments
- [1409.0473] Neural Machine Translation by Jointly Learning to Align and Translate http://arxiv.org/abs/1409.0473 0 comments
- vLLM: Easy, Fast, and Cheap LLM Serving with PagedAttention | vLLM Blog https://blog.vllm.ai/2023/06/20/vllm.html 0 comments
- Fast JSON Decoding for Local LLMs with Compressed Finite State Machine | LMSYS Org https://lmsys.org/blog/2024-02-05-compressed-fsm/ 0 comments
- Welcome to vLLM! — vLLM https://docs.vllm.ai/en/latest/ 0 comments
- GitHub - noamgat/lm-format-enforcer: Enforce the output format (JSON Schema, Regex etc) of a language model https://github.com/noamgat/lm-format-enforcer 0 comments
- GitHub - dottxt-ai/outlines: Structured Text Generation https://github.com/dottxt-ai/outlines 0 comments
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