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01xedro98 /quantization-as-a-transfer-constraint Quantization as a Transfer Constraint: Zero-Shot Learning-Rate Transfer Survives Low Precision, but muP's Stability Margin Collapses Author: Shubhankar Kahali - Trumbo Labs, Inc - shubhankar@trumbo.dev License: CC BY 4.0 Paper: paper/quant_transfer_arxiv.pdf Abstract Maximal update parametrization (muP) licenses zero-shot hyperparameter transfer in exact arithmetic, but low-precision training perturbs precisely the coordinate magnitudes muP is designed to keep… See the full description on the dataset page: https://huggingface.co/datasets/xedro98/quantization-as-a-transfer-constraint.tabularother1K<n<10K1 likes79 downloads28d agoHugging Face02derekl35 /quantization-benchmarkstabularn<1K3 likes66 downloads1y agoHugging Face03mkvn /quantization-cache-amplification Quantization as Cache Amplification Trillion-Parameter Mixture-of-Experts Inference on a Commodity Laptop Kavin Kumar, Neural Metrics 📄 Read the paper — 11 pages What this is Weight quantization is usually justified as footprint reduction. This work argues that for offloaded mixture-of-experts inference that framing misses the leverage. The binding resource is not storage capacity but the fraction of expert slots resident in DRAM — and storage traffic depends on… See the full description on the dataset page: https://huggingface.co/datasets/mkvn/quantization-cache-amplification.documentn<1K0 likes64 downloads1mo agoHugging Face04MangoLab /EXAONE-4.0-1.2B-Quantization-MMLUtabularn<1K1 likes47 downloads8mo agoHugging Face05nielsr /r3al-vit-quantization-codex-trace R3AL ViT Quantization — Codex Agent Trace Codex session trace for installing the R3AL CLI and agent skill, exporting google/vit-base-patch16-224 to ONNX, performing dynamic INT8 post-training quantization on R3AL, and evaluating model size, Apple-arm64 CPU latency, and prediction fidelity on a 100-image ImageNet validation sample. The original Codex JSONL format is preserved for Hugging Face's native Agent Trace viewer. Credential values, email addresses, unrelated Gmail/Slack… See the full description on the dataset page: https://huggingface.co/datasets/nielsr/r3al-vit-quantization-codex-trace.tabularn<1K0 likes47 downloads1mo agoHugging Face06sixstringzen /hemmingway-1-omlx-quantization-benchmark-v1 Hemmingway-1 oMLX Quantization Benchmark This is the public-safe benchmark package for the Hemmingway-1 oMLX quantization study on Apple Silicon. The release contains the authored task prompts, selected local execution metadata, aggregate blind-judge results, reliability metadata, and the policy used to select records when a condition was run more than once. What is in the dataset File Rows Purpose data/train.jsonl 184 Mixed rows. Filter record_type for… See the full description on the dataset page: https://huggingface.co/datasets/sixstringzen/hemmingway-1-omlx-quantization-benchmark-v1.tabulartext-generationn<1K0 likes46 downloads8h agoHugging Face07KwabsHug /repro-robuq-pushing-dits-to-w1-58a2-via-robust-activation-quantization-traces Agent traces Agent sessions published from a Trackio Logbook. tabularn<1K0 likes43 downloads2mo agoHugging Face08beatsprom /llm-quantization-fine-tuning-2026 ⚡ LLM Fine-Tuning, Quantization & Model Optimization Dataset (2023–2026) This dataset contains 100 sample audit-verified research papers focusing on Large Language Model (LLM) quantization (GPTQ, AWQ, GGUF), fine-tuning (LoRA, QLoRA, PEFT), pruning, distillation, and speculative decoding. 📊 Features: 384-dimensional PyTorch Embeddings (all-MiniLM-L6-v2) for instant Vector Search NLP Sentence Extraction: Real extracted core problems & key technical innovations… See the full description on the dataset page: https://huggingface.co/datasets/beatsprom/llm-quantization-fine-tuning-2026.tabulartext-classificationn<1K0 likes42 downloads1mo agoHugging Face09taozi555 /fp8-quantizationtabular1K<n<10K0 likes20 downloads2y agoHugging Face10ssakethch /h200-quantization-benchmarks H200 Quantization Benchmarks Benchmark results for 40 quantized and non-quantized instruction-tuned LLMs evaluated on an NVIDIA H200 MIG (Multi-Instance GPU) setup. This dataset supports reproducible comparison of quantization methods (AWQ, GPTQ, fp8, bf16) across accuracy and throughput dimensions. Dataset Configs Config Description Rows accuracy Per-task accuracy results from lm-eval across all models ~240 accuracy_leaderboard Aggregated accuracy… See the full description on the dataset page: https://huggingface.co/datasets/ssakethch/h200-quantization-benchmarks.tabularn<1K1 likes17 downloads5mo agoHugging Face11derekl35 /diffusers-quantization-benchmarkstabularn<1K0 likes16 downloads1y agoHugging Face12harpreetsahota /quantization_experiment_resultstabularn<1K1 likes10 downloads3y agoHugging Face

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