untrained
tiny-untrained-graniteoktrained_-_llama-3.1-0.5B-Untrained-gguflmlab_-_lmlab-mistral-1b-untrained-ggufAarushhh_-_untrained-pruned-customffn-llama3.1-8b-large-ggufAarushhh_-_untrained-Qwen-2.5-7b-Instruct-Pruned-gguforig_btx_endo_rex_pathgen_qwen25_vl_3b-untrainedflex_merged_endo_rex_path_btx_untrainedAarushhh_-_untrained-suave-789M-gguf
persian-asr-untrained-embeddings-v1
Persian ASR Untrained Corpus Embeddings v1
This dataset stores manifest and embedding artifacts for Persian ASR data mining.
The corpus is intended for acoustic/textual clustering, diversity selection, noise/environment mining, and training-data planning for VisualEars-style robust Persian ASR.
Contents
manifests/all_untrained_manifest.v1.jsonl: canonical row/file manifest after excluding known trained/eval content where available.… See the full description on the dataset page: https://huggingface.co/datasets/Reza2kn/persian-asr-untrained-embeddings-v1.details_Inv__MoECPM-Untrained-4x2b
Dataset Card for Evaluation run of Inv/MoECPM-Untrained-4x2b
Dataset automatically created during the evaluation run of model Inv/MoECPM-Untrained-4x2b 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 is always pointing to the… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_Inv__MoECPM-Untrained-4x2b.Untrainedv2Untrainedpepsi-2021-10k-8192-without-year-thinking-1-with-untrained-cartridge
Dataset: Phudish/pepsi-2021-10k-8192-without-year-thinking-1-with-untrained-cartridge
Usage
from datasets import load_dataset
ds = load_dataset("Phudish/pepsi-2021-10k-8192-without-year-thinking-1-with-untrained-cartridge")
amd-2022-10k-8192-without-year-thinking-1-with-untrained-cartridge
Dataset: Phudish/amd-2022-10k-8192-without-year-thinking-1-with-untrained-cartridge
Usage
from datasets import load_dataset
ds = load_dataset("Phudish/amd-2022-10k-8192-without-year-thinking-1-with-untrained-cartridge")