Tweeting about new Adapters on @AdapterHub | Bot 🤖
Joined June 2020
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AdapterHub Bert retweeted
📢 New preprint 🎉
We - the AdapterHub team - present the M2QA benchmark to evaluate joint domain and language transfer!
🔬 Key highlight: We show that adapter-based methods on small language models can reach the performance of Llama 3 on M2QA! 🚀
👇
📢 New preprint 🎉
We introduce "M2QA: Multi-domain Multilingual Question Answering", a benchmark for evaluating joint language and domain transfer.
We present 5 key findings - one of them: Current transfer methods are insufficient, even for LLMs!
📜arxiv.org/abs/2407.01091
🧵👇
AdapterHub Bert retweeted
🚀Wanna help us shape the future of the adapters library?🔎Take our survey!✏️
🧠Your input is crucial in planning our next steps. Share your thoughts in a 5 min. survey and help us enhance features of the library and extend it based on your needs!
--> forms.gle/yf8Cd6HC4qWkMDxFA
12 new Adapters for models xlm-roberta-large, xlm-roberta-base, bert-base-multilingual-cased by @yyyyyyyyifan for tasks mlki/es, mlki/ts, mlki/tp and more!
Here's one to check out: adapterhub.ml/adapters/mlki/…
New Adapter by @https://teapawt.net/kabirahuja004:
Pfeiffer adapter stacked on top of language adapter for the NLI task.
Check it out at adapterhub.ml/adapters/kabir…
New Adapter by @kalpeshk2011:
This adapter has been trained on the English formality classification GYAFC dataset and tested with other language adapters (like hindi) for zero-shot transfer.
Check it out at adapterhub.ml/adapters/marti…
New Adapter by @clifapt:
Adapter for mbart-large-cc25 in Pfeiffer architecture with reduction factor 2 trained on the WMT16 Romanian-English translation task.
Check it out at adapterhub.ml/adapters/ukp/f…
16 new Adapters for model gpt2 by @h_sterz for tasks sentiment/sst-2, nli/qnli, nli/rte and more!
Here's one to check out: adapterhub.ml/adapters/ukp/g…
22 new Adapters for model bert-base-multilingual-cased by @PfeiffJo for tasks wikiann/en, zh_yue/wiki, cs/wiki and more!
Here's one to check out: adapterhub.ml/adapters/ukp/b…
AdapterHub Bert retweeted
This is AdapterHub-Bart, our new team member & @AdapterHubBert's best friend. Say Hi & meet him at AdapterHub.ml
ALT AdapterHub-Bart
16 new Adapters for model facebook/bart-base by @clifapt for tasks nli/qnli, lingaccept/cola, sts/mrpc and more!
Here's one to check out: adapterhub.ml/adapters/ukp/f…
4 new Adapters for model facebook/bart-large by @clifapt for tasks sum/cnn_dailymail, sum/xsum
Here's one to check out: adapterhub.ml/adapters/ukp/f…
25 new Adapters for model distilbert-base-uncased by @clifapt for tasks sentiment/sst-2, rc/race, rc/multirc and more!
Here's one to check out: adapterhub.ml/adapters/ukp/d…
New Adapter by @Hannah70676760:
Adapter trained on the CoNLL2003 dataset for named entity recognition
.
Check it out at adapterhub.ml/adapters/ukp/b…
New Adapter by @arueckle:
Our adapters from the MultiCQA paper (https://arxiv.
Check it out at adapterhub.ml/adapters/ukp/b…
AdapterHub Bert retweeted
Check out our paper “AdapterDrop"!
We find that Adapters can train 60% faster than full fine-tuning. With AdapterDrop we increase inference speed by up to 36% for 8 parallel tasks.
GGeigle @Maxxx216 @devnull90 @PfeiffJo NReimers IGurevych @AdapterHub
arxiv.org/pdf/2010.11918.pdf
AdapterHub Bert retweeted
In our new paper we show that randomly dropping out adapters during training results in a robust dynamically scalable model!
Also adapter weights can be shared across layers 😲
Check it out 👇
Check out our paper “AdapterDrop"!
We find that Adapters can train 60% faster than full fine-tuning. With AdapterDrop we increase inference speed by up to 36% for 8 parallel tasks.
GGeigle @Maxxx216 @devnull90 @PfeiffJo NReimers IGurevych @AdapterHub
arxiv.org/pdf/2010.11918.pdf
New Adapter by @NirantK, @meghanabhange:
Adapter for Hinglish Sentiment Analysis, based on SemEval 2020 Task 9.
Check it out at adapterhub.ml/adapters/niran…
4 new Adapters by @clifapt for task qa/squad2
Here's one to check out: adapterhub.ml/adapters/ukp/b…
New Adapter by @mapmeld:
Adapter for AraBERT (aubmindlab/bert-base-arabert) trained to classify Arabic by dialect, trained for 3 epochs on samples from University of British Columbia and John Hopkins University.
Check it out at adapterhub.ml/adapters/mapme…
4 new Adapters by @clifapt for task qa/squad1
Here's one to check out: adapterhub.ml/adapters/ukp/b…