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The original code is from https://github.com/memray/seq2seq-keyphrase-pytorch, which is used to do keyphrase generation using seq2seq with attention model.
The main features of whqwill/seq2seq-keyphrase-bert are: Model Utilities.
Open-source alternatives to whqwill/seq2seq-keyphrase-bert include: arcee-ai/mergekit — MergeKit is a toolkit for combining multiple pre-trained large language models into a single entity using algorithmic… facebookresearch/llm-transparency-tool — LLM Transparency Tool (LLM-TT), an open-source interactive toolkit for analyzing internal workings of… guotong1988/bert-chinese. hanxiao/bert-as-service — This project is a high-performance BERT embedding service and inference server designed to map text sequences into… harishsg993010/llm-reasoner — Make any LLM to think deeper like OpenAI o1 and deepseek R1! algteam/bert-examples — BERT：google-BERT.
MergeKit is a toolkit for combining multiple pre-trained large language models into a single entity using algorithmic blending. It provides a specialized system for parameter interpolation and weight extraction to unify model capabilities. The project distinguishes itself through an evolutionary merge optimizer that tunes parameters based on quantitative evaluation metrics. It also features a mixture of experts orchestrator capable of converting dense models into sparse architectures and a tokenizer alignment tool for transplanting embeddings between different models. The toolkit covers a br
LLM Transparency Tool (LLM-TT), an open-source interactive toolkit for analyzing internal workings of Transformer-based language models. Check out demo at https://huggingface.co/spaces/facebook/llm-transparency-tool-demo
