datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
vlm-info-loss-results
VLM Grounding Evaluation Results
Grounding evaluation results for vision-language models on robotics manipulation datasets.
Part of the vlm-info-loss project studying
how VLM connectors transform visual representations.
Background
Our embedding-level analysis shows VLM connectors perform a compress-then-expand transformation:
they sharpen dominant-object representations while compressing secondary-object category identity.
All tested models converge to ~83%… See the full description on the dataset page: https://huggingface.co/datasets/MicroAGI-Labs/vlm-info-loss-results.qwen36-kquant-offload-mtp-swebench-lite100-results
Qwen3.6 K-Quant Offload MTP SWE-bench Lite 100 Results
This dataset contains the complete 5-model x 100-prompt runtime benchmark artifacts plus a detailed statistical analysis layer.
Primary conclusion: hot30/cold30 was the best decode-throughput run, while Q4_K_M had the best total wall clock. The ATX hot30/cold30 quantization significantly outperformed both Q4_K_M and Q3_K_XL on paired decode throughput, but Q4_K_M remains the elapsed-time control.
The ATX/K3 hot10, hot20, and… See the full description on the dataset page: https://huggingface.co/datasets/jakeatx/qwen36-kquant-offload-mtp-swebench-lite100-results.sae-jailbreaks-resultsbrittleness-results
Adapters copied (2026-09-08). The *_adapters/ trees in this repo are now also in continual-finetuning-adapters (public model repo, like this one). Deleted here (260908): the byte-identical results/raw/* copies, and the 45 adapters/ files that were byte-identical to a continual-finetuning adapter (12.3 GB); both lists are in MIGRATION_260908.md of any new repo. Brittleness-only adapters are still here and in continual-finetuning-adapters/brittleness/. Please prefer the new repo for loading.… See the full description on the dataset page: https://huggingface.co/datasets/false-facts-finetuning/brittleness-results.pokemon-llm-svg-bench-results
Pokémon LLM SVG Bench (V1.1)
This is a snapshot of scored SVG drawings from the Pokémon LLM SVG Bench — LLMs try to draw Pokémon in SVG, and we score the results. Prefer reading the live site for context; for scoring rules and methodology, see About.
Unofficial fan / research project. Pokémon images are copyrighted by The Pokémon Company and related companies involved in developing, operating, and managing the Pokémon series. Pokémon descriptions are sourced from… See the full description on the dataset page: https://huggingface.co/datasets/haxfenx/pokemon-llm-svg-bench-results.eval_results_libero_10_qwen