Pushed by DataDreamer
Browse filesUpdate datadreamer.json
- datadreamer.json +61 -0
datadreamer.json
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| 1 |
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{
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"model_card": {
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"Date & Time": "2024-11-21T07:37:17.604673",
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"Model Card": [
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"https://huggingface.co/FacebookAI/xlm-roberta-base"
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],
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"License Information": [
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"mit"
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],
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"Citation Information": [
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"\n@inproceedings{Wolf_Transformers_State-of-the-Art_Natural_2020,\n author = {Wolf, Thomas and Debut, Lysandre and Sanh, Victor and Chaumond, Julien",
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| 12 |
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"\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",
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| 13 |
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"@article{DBLP:journals/corr/abs-1911-02116,\n author = {Alexis Conneau and\n Kartikay Khandelwal and\n Naman Goyal and\n Vishrav Chaudhary and\n Guillaume Wenzek and\n Francisco Guzm{\\'{a}}n and\n Edouard Grave and\n Myle Ott and\n Luke Zettlemoyer and\n Veselin Stoyanov},\n title = {Unsupervised Cross-lingual Representation Learning at Scale},\n journal = {CoRR},\n volume = {abs/1911.02116},\n year = {2019},\n url = {http://arxiv.org/abs/1911.02116},\n eprinttype = {arXiv},\n eprint = {1911.02116},\n timestamp = {Mon, 11 Nov 2019 18:38:09 +0100},\n biburl = {https://dblp.org/rec/journals/corr/abs-1911-02116.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}",
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"@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}"
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]
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},
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"data_card": {
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| 18 |
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"Get SynthSTEL Training Triplets Dataset": {
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"Date & Time": "2024-11-20T18:38:17.601393",
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"Dataset Name": [
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"StyleDistance/mstyledistance_training_triplets"
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],
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"Dataset Card": [
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"https://huggingface.co/datasets/StyleDistance/mstyledistance_training_triplets"
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]
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},
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"Get SynthSTEL Training Triplets Dataset (train split)": {
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"Date & Time": "2024-11-20T18:57:23.493502"
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},
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| 30 |
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"Get SynthSTEL Training Triplets Dataset (train split) (shuffle)": {
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| 31 |
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"Date & Time": "2024-11-21T07:03:58.565828"
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}
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},
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"__version__": "0.35.0",
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"datetime": "2024-11-21T07:03:59.772515",
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"type": "TrainSentenceTransformer",
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"name": "Train StyleDistance Model",
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"version": 1.0,
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"fingerprint": "ed4b8ecf9a7f20e2",
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| 40 |
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"req_versions": {
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"dill": "0.3.8",
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| 42 |
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"sqlitedict": "2.1.0",
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"torch": "2.3.1",
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"numpy": "1.26.4",
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| 45 |
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"transformers": "4.40.1",
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| 46 |
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"datasets": "2.17.0",
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| 47 |
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"huggingface_hub": "0.23.4",
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| 48 |
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"accelerate": "0.32.1",
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| 49 |
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"peft": "0.11.1",
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| 50 |
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"tiktoken": "0.7.0",
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| 51 |
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"tokenizers": "0.19.1",
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"openai": "1.35.13",
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| 53 |
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"ctransformers": "0.2.27",
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| 54 |
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"optimum": "1.21.2",
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"bitsandbytes": "0.43.1",
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"litellm": "1.31.14",
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| 57 |
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"trl": "0.8.1",
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"setfit": "1.0.3"
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},
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"interpreter": "3.10.9 (main, Apr 17 2023, 21:32:03) [GCC 7.5.0]"
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}
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