ERNIE
K-BERT
ERNIE | K-BERT | |
---|---|---|
4 | 1 | |
6,165 | 935 | |
0.0% | - | |
2.7 | 10.0 | |
about 1 year ago | over 1 year ago | |
Python | Python | |
Apache License 2.0 | - |
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.
ERNIE
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[N] Baidu to Unveil Conversational AI ERNIE Bot on March 16 (Live)
Found relevant code at https://github.com/PaddlePaddle/ERNIE + all code implementations here
- ERNIE - ViLG 2.0 by Baidu
- [R] Baidu’s Knowledge-Enhanced ERNIE 3.0 Pretraining Framework Delivers SOTA NLP Results, Surpasses Human Performance on the SuperGLUE Benchmark
K-BERT
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[D] Papers that inject embeddings into LMs
Found relevant code at https://github.com/autoliuweijie/K-BERT + all code implementations here
What are some alternatives?
unilm - Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
ERNIE-text-classification-pytorch - This repo contains a PyTorch implementation of a pretrained ERNIE model for text classification.
ABSA-PyTorch - Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析,使用PyTorch实现。
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
PaddleNLP - 👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.
clip-as-service - 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
BERT-pytorch - Google AI 2018 BERT pytorch implementation
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.