LFM3 1.7B 1 GB GGUF + EAR98 GGUF
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LFM3 1.7B 1 GB GGUF + EAR98 GGUF I used RCO and GSQ to produce two improved GGUF checkpoints. RCO directly optimized EAR as its objective. All reported EAR scores were computed on a held-out dataset. Both GGUFs significantly outperform their respective donor GGUFs of similar size from LiquidAI and AtomicChat. I also computed EAR in French, Japanese, and Hindi, where the impact of quantization is more pronounced. Good reminder that quantization typically causes greater performance degradation on non-English tasks. Checkpoints and results: https://huggingface.co/kaitchup/LFM3-1.7B-GSQ-GGUF
Posted by Benjamin Marie (7.6k followers) 2 h ago · 12 likes · 807 views · view the original post on X. Kept by the Dev Radar as Other. Tools mentioned: lfm3-1.7b-gsq-gguf.
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