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Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.

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01ReadyAi /5000-podcast-conversations-with-metadata-and-embedding-dataset 🗂️ ReadyAI - 5,000 Podcast Conversations with Metadata and Embedding Dataset ReadyAI, operating subnet 33 on the Bittensor Network is an open-source initiative focused on low-cost, resource-minimal pipelines for structuring raw data for AI applications. This dataset is part of the ReadyAI Conversational Genome Project, leveraging the Bittensor decentralized network. AI runs on structured data — and this dataset bridges the gap between raw conversation transcripts and structured… See the full description on the dataset page: https://huggingface.co/datasets/ReadyAi/5000-podcast-conversations-with-metadata-and-embedding-dataset.text10K<n<100K8 likes1.2k downloads1y agoHugging Face02talkpl-ai /TalkPlayData-Extra-metadata-qwen3_embedding_0.6btext1M<n<10M0 likes87 downloads9mo agoHugging Face03bluuebunny /crossref_metadata_embeddings_split_2025Created vector embeddings for the abstract field for the dataset: bluuebunny/crossref_metadata_2025_split using mixedbread-ai/mxbai-embed-large-v1 textsentence-similarity10M<n<100M0 likes73 downloads1y agoHugging Face04bluuebunny /crossref_metadata_embeddings_split_2025_binaryCreated vector embeddings for the abstract field for the dataset: bluuebunny/crossref_metadata_2025_split using mixedbread-ai/mxbai-embed-large-v1 and binarised it using: # Function to binarise float embeddings def binarise(row): # Make it a numpy array, since batching sends it as list float_vector = np.array(row['vector'], dtype=np.float32) # Binarise binary_vector = np.where(float_vector >= 0, 1, 0) # Pack it to make it milvus compatible row['vector'] =… See the full description on the dataset page: https://huggingface.co/datasets/bluuebunny/crossref_metadata_embeddings_split_2025_binary.textsentence-similarity10M<n<100M0 likes42 downloads1y agoHugging Face05librarian-bots /dataset_cards_with_metadata_with_embeddingstabular10K<n<100K1 likes32 downloads3y agoHugging Face06wenbopan /metadata_embeddingtext10K<n<100K0 likes22 downloads2y agoHugging Face07librarian-bots /model_cards_with_metadata_with_embeddings Dataset Card for Hugging Face Hub Model Cards with Embeddings This dataset consists of model cards for models hosted on the Hugging Face Hub. The model cards are created by the community and provide information about the model, its performance, its intended uses, and more. This dataset is updated on a daily basis and includes publicly available models on the Hugging Face Hub. This dataset is made available to help support users wanting to work with a large number of Model Cards… See the full description on the dataset page: https://huggingface.co/datasets/librarian-bots/model_cards_with_metadata_with_embeddings.tabulartext-retrieval100K<n<1M5 likes16 downloads3y agoHugging Face08MisterHjj /Embedding_metadata_steamtabular100K<n<1M0 likes11 downloads9mo agoHugging Face

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