Official PyTorch implementation of "GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance" (ICML 2025)
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Apr 13, 2026 - Python
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llm-quantization
Here are 12 public repositories matching this topic...
[CAAI AIR'24] Minimize Quantization Output Error with Bias Compensation
post-training-quantization llm-compression output-error-optimization bias-compensation llm-quantization
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Mar 12, 2025 - Python
Open quantization tooling for TurboQuant-style low-bit LLM releases, stock GGUF deployment, and Apple Silicon runtime experiments.
apple toolkit tooling tensor quantization apple-silicon llm llm-inference gguf llm-quantization turboquant
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May 5, 2026 - Python
Enable expert-level, multi-step diagnostic reasoning in Claude Code with an easy-to-use skill for clear and explainable AI diagnosis.
github python shell bash aws ansible terminal ai terraform esp32 infrastructure-as-code troubleshooting multi-agent-systems kernal llm langchain peft-fine-tuning-llm llm-quantization diagnostic-reasoning transparent-reasoning-flows
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May 10, 2026 - Python
A more deep research about TurboQuant algorithms
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Apr 6, 2026 - Python
Shift-based post-training quantization analysis for LLMs (ShiftQuant paper)
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Mar 28, 2026 - Python
Let me make GGUF files quickly
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Jun 4, 2025 - Python
LLM quantization project built around `llama.cpp` + `Ollama` + `GGUF`
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Mar 22, 2026 - Python
PentaNet extends BitNet's ternary quantization to pentanary {-2,-1,0,+1,+2}, improving perplexity by 6.4% at 124M params while preserving zero-multiplier arithmetic.
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Apr 17, 2026 - Python
Develop an on-device AI system that processes and analyzes complaints using lightweight, fine-tuned LLMs optimized for industrial field use.
nlp transformers pytorch fine-tuning capstone-project edge-ai github-config on-device-ai llm llm-quantization industry-collaboration
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May 10, 2026 - Python
Implementation of advanced Natural Language Processing architectures and optimization techniques, built from scratch. The projects focus on understanding the internal mechanics of Transformers, LLM efficiency through quantization, and scaling via Mixture-of-Experts (MoE).
load-balancing mixture-of-experts transformer-architecture positional-encoding llm-fine-tuning llm-quantization
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Jan 8, 2026 - Python
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