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User tests Meta's Muse Glimmer 30B on a 2× DGX Spark cluster, extending context from 131K to 1M tokens with YaRN and confirming passing retrieval at 832K tokens. Reports ~3× speedup from DFlash speculative decoding and shares full config.
Jet-Long introduces a tuning-free zero-shot method for extending LLM context length by dynamically adjusting RoPE scaling, achieving strong performance on benchmarks up to 128K context with minimal inference overhead.
EndPrompt proposes a method for extending the context window of large language models using only short training sequences, by anchoring a terminal prompt with target-length positional indices. It achieves strong benchmark results with substantially less computation than full-length fine-tuning.