gector
DeBERTa
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| gector | DeBERTa | |
|---|---|---|
| 2 | 4 | |
| 863 | 1,844 | |
| 1.4% | 2.5% | |
| 0.0 | 3.6 | |
| 9 months ago | 7 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
gector
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ML application for grammar correction
If you capture it, you might as well correct it. Check out Gramformer or Grammarly's Gector. You can do scoring based on number of mistakes proposed by these models i.e. the fewer, the better.
- Is there any way to detect grammatical errors and classify text as being either grammatically correct/incorrect?
DeBERTa
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🚀 Microsoft AI Introduce DeBERTa-V3: A Novel Pre-Training Paradigm for Language Models Based on the Combination of DeBERTa and ELECTRA
Quick Read: https://www.marktechpost.com/2023/03/23/microsoft-ai-introduce-deberta-v3-a-novel-pre-training-paradigm-for-language-models-based-on-the-combination-of-deberta-and-electra/ Paper: https://arxiv.org/pdf/2111.09543.pdf Github: https://github.com/microsoft/DeBERTa
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How do I fine-tune zero shot models?
The obvious answer is to look at how the Deberta model was trained for MNLI and copy that: github
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[D] Paper Explained - DeBERTa: Decoding-enhanced BERT with Disentangled Attention (Full Video Analysis)
Code: https://github.com/microsoft/DeBERTa
- DeBERTa-0.9b/1.5b checkpoints released (SuperGLUE score: 89.9%)
What are some alternatives?
Gramformer - A framework for detecting, highlighting and correcting grammatical errors on natural language text. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
clip-as-service - 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
spark-nlp - State of the Art Natural Language Processing
BERTweet - BERTweet: A pre-trained language model for English Tweets (EMNLP-2020)
happy-transformer - Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
adaptnlp - An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
sapbert - [NAACL'21 & ACL'21] SapBERT: Self-alignment pretraining for BERT & XL-BEL: Cross-Lingual Biomedical Entity Linking.
spokestack-python - Spokestack is a library that allows a user to easily incorporate a voice interface into any Python application with a focus on embedded systems.