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CLEX: Continuous Length Extrapolation for Large Language Models
Paper • 2310.16450 • Published • 9 -
E^2-LLM: Efficient and Extreme Length Extension of Large Language Models
Paper • 2401.06951 • Published • 24 -
Data Engineering for Scaling Language Models to 128K Context
Paper • 2402.10171 • Published • 21
Juan Herrera
juampahc
AI & ML interests
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3
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Transformers are Multi-State RNNs
Paper • 2401.06104 • Published • 35 -
Linear Transformers with Learnable Kernel Functions are Better In-Context Models
Paper • 2402.10644 • Published • 78 -
In Search of Needles in a 10M Haystack: Recurrent Memory Finds What LLMs Miss
Paper • 2402.10790 • Published • 40 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 602
models
6
juampahc/bge-m3-m2v-758
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1
juampahc/bge-m3-m2v-256
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13
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1
juampahc/bge-m3-m2v-1024
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2
juampahc/bge-m3-baai-onnx
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3.11k
juampahc/bge-m3-baai-quant-opt
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200
juampahc/bge-m3-baai-quant
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1.15k
datasets
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