quantized
quantized-llama-3.1-leaderboard-v2-evals
Open LLM Leaderboard v2 Benchmark Results
This artifact contains all the data from evaluations of Neural Magic's quantized Llama-3.1 models.
These evaluations were produced with lm-evaluation-harness by running the following command:
lm_eval \
--model vllm \
--model_args pretrained="<model_path>",dtype=auto,add_bos_token=False,max_model_len=4096,tensor_parallel_size="<num_gpus>",gpu_memory_utilization=0.8,enable_chunked_prefill=True \
--apply_chat_template \… See the full description on the dataset page: https://huggingface.co/datasets/neuralmagic/quantized-llama-3.1-leaderboard-v2-evals.quantized-retrieval-dataimagenet-sdxl-quantized
ImageNet SDXL Quantized
This repository provides the ImageNet-1K dataset pre-encoded with the Stable Diffusion XL VAE encoder and quantized to uint8, allowing for faster training of latent diffusion models by eliminating the need for on-the-fly encoding.
Key Features
Reduces quantization error by 2dB PSNR compared to a linear encoding scheme
Provided in both 256 and 512 resolutions
Compatible with NumPy, JAX, and PyTorch
Usage
Loading the dataset… See the full description on the dataset page: https://huggingface.co/datasets/jon-kyl/imagenet-sdxl-quantized.ToneWebinars_quantized-bigcodecdaily-paper-2026-08-20-quantized-embedding-skill-router
Quantizing the Gatekeeper: Accuracy-Cost Tradeoffs of Compressing the Embedding Model in Hybrid Skill Routers
TL;DR — Quantizing the dense embedding half of a hybrid (BM25 + embedding) skill router to INT8 leaves fused hit@1/hit@3 unchanged on a multilingual stand-in encoder because the lexical term dampens the error, but an off-the-shelf dynamic quantization backend made single-query encoding slower rather than faster on CPU, failing the latency side of the compression's own… See the full description on the dataset page: https://huggingface.co/datasets/thaki-AI/daily-paper-2026-08-20-quantized-embedding-skill-router.details_dball__zephyr-tiny-sft-qlora-quantized-2
Dataset Card for Evaluation run of dball/zephyr-tiny-sft-qlora-quantized-2
Dataset automatically created during the evaluation run of model dball/zephyr-tiny-sft-qlora-quantized-2 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_dball__zephyr-tiny-sft-qlora-quantized-2.