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lmqg/mt5-base-dequad-qg
lmqg
mt5
20
189
transformers
0
text2text-generation
true
false
false
cc-by-4.0
['de']
['lmqg/qg_dequad']
null
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0
0
0
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['question generation']
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# Model Card of `lmqg/mt5-base-dequad-qg` This model is fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) for question generation task on the [lmqg/qg_dequad](https://huggingface.co/datasets/lmqg/qg_dequad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-gener...
4de004e2d0863e5beafbb7d59a3a40dd
Mirelle/t5-small-finetuned-ro-to-en
Mirelle
t5
12
3
transformers
0
text2text-generation
true
false
false
apache-2.0
null
['wmt16']
null
0
0
0
0
0
0
0
['generated_from_trainer']
true
true
true
2,570
false
<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # t5-small-finetuned-ro-to-en This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wmt16 datas...
65b8db644725c27cb897b9fe58105171
google/multiberts-seed_0-step_60k
google
bert
8
15
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0
null
true
true
false
apache-2.0
['en']
null
null
0
0
0
0
0
0
0
['multiberts', 'multiberts-seed_0', 'multiberts-seed_0-step_60k']
false
true
true
3,515
false
# MultiBERTs, Intermediate Checkpoint - Seed 0, Step 60k MultiBERTs is a collection of checkpoints and a statistical library to support robust research on BERT. We provide 25 BERT-base models trained with similar hyper-parameters as [the original BERT model](https://github.com/google-research/bert) but with different...
91c2d4e2078ff630fa229149d0079a86
jonfd/electra-base-igc-is
jonfd
electra
7
2
transformers
0
null
true
false
false
cc-by-4.0
['is']
['igc']
null
0
0
0
0
0
0
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[]
false
true
true
607
false
# Icelandic ELECTRA-Base This model was pretrained on the [Icelandic Gigaword Corpus](http://igc.arnastofnun.is/), which contains approximately 1.69B tokens, using default settings. The model uses a WordPiece tokenizer with a vocabulary size of 32,105. # Acknowledgments This research was supported with Cloud TPUs fro...
60559a876ff24f32f3df16dfa8098623
kingery/hyc-06-512-sd15-2e-6-1500-man-ddim
kingery
null
24
5
diffusers
0
text-to-image
false
false
false
creativeml-openrail-m
null
null
null
1
1
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['text-to-image']
false
true
true
1,590
false
### hyc-06-512-sd15-2e-6-1500-man-ddim on Stable Diffusion via Dreambooth #### model by kingery This your the Stable Diffusion model fine-tuned the hyc-06-512-sd15-2e-6-1500-man-ddim concept taught to Stable Diffusion with Dreambooth. It can be used by modifying the `instance_prompt`: **a photo of yangguangkechuang man...
c5bc3c056f2003e62d438f0ac7ee4d71
hassnain/wav2vec2-base-timit-demo-colab3
hassnain
wav2vec2
16
5
transformers
0
automatic-speech-recognition
true
false
false
apache-2.0
null
null
null
0
0
0
0
0
0
0
['generated_from_trainer']
true
true
true
1,462
false
<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # wav2vec2-base-timit-demo-colab3 This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/w...
7aadba30b8a9bb4f9dbe3869edbbc0a1