| { | |
| "model_card": { | |
| "Date & Time": "2025-03-29T08:36:58.409267", | |
| "Model Card": [ | |
| "https://huggingface.co/BAAI/bge-m3" | |
| ], | |
| "License Information": [ | |
| "mit" | |
| ], | |
| "Citation Information": [ | |
| "\n@inproceedings{Wolf_Transformers_State-of-the-Art_Natural_2020,\n author = {Wolf, Thomas and Debut, Lysandre and Sanh, Victor and Chaumond, Julien", | |
| "\n@Misc{peft,\n title = {PEFT: State-of-the-art Parameter-Efficient Fine-Tuning methods},\n author = {Sourab Mangrulkar and Sylvain Gugger and Lysandre Debut and Younes", | |
| "@misc{bge-m3,\n title={BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation}, \n author={Jianlv Chen and Shitao Xiao and Peitian Zhang and Kun Luo and Defu Lian and Zheng Liu},\n year={2024},\n eprint={2402.03216},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}", | |
| "@inproceedings{reimers-2019-sentence-bert,\n title = \"Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks\",\n author = \"Reimers, Nils and Gurevych, Iryna\",\n booktitle = \"Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing\",\n month = \"11\",\n year = \"2019\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://arxiv.org/abs/1908.10084\",\n}" | |
| ] | |
| }, | |
| "data_card": { | |
| "Get Matching Calibration v2": { | |
| "Date & Time": "2025-03-26T09:39:28.181485", | |
| "Dataset Name": [ | |
| "fineinstructions/matching_calibration_v2" | |
| ], | |
| "Dataset Card": [ | |
| "https://huggingface.co/datasets/fineinstructions/matching_calibration_v2" | |
| ] | |
| }, | |
| "Create labels": { | |
| "Date & Time": "2025-03-26T09:49:41.491446" | |
| }, | |
| "Filter out the too long rows": { | |
| "Date & Time": "2025-03-26T09:55:24.242992" | |
| }, | |
| "Filter out the too long rows (train split)": { | |
| "Date & Time": "2025-03-26T10:15:32.264497" | |
| } | |
| }, | |
| "__version__": "0.46.0", | |
| "datetime": "2025-03-28T23:33:08.582718", | |
| "type": "CoverageTrainSentenceTransformer", | |
| "name": "Train Matching Embedding", | |
| "version": 1.0, | |
| "fingerprint": "fb45010b668e97dc", | |
| "req_versions": { | |
| "dill": "0.3.8", | |
| "sqlitedict": "2.1.0", | |
| "torch": "2.5.1", | |
| "numpy": "1.26.4", | |
| "transformers": "4.48.2", | |
| "datasets": "3.2.0", | |
| "huggingface_hub": "0.27.1", | |
| "accelerate": "1.3.0", | |
| "peft": "0.14.0", | |
| "tiktoken": "0.7.0", | |
| "tokenizers": "0.21.0", | |
| "openai": "1.59.8", | |
| "ctransformers": "0.2.27", | |
| "optimum": "1.23.3", | |
| "bitsandbytes": "0.45.0", | |
| "litellm": "1.57.8", | |
| "trl": "0.9.6", | |
| "setfit": "1.1.1", | |
| "vllm": "0.7.0" | |
| }, | |
| "interpreter": "3.11.1 (main, Apr 12 2023, 13:34:00) [GCC 7.5.0]" | |
| } |