mim-solutions / bert_for_longer_textsLinks
BERT classification model for processing texts longer than 512 tokens. Text is first divided into smaller chunks and after feeding them to BERT, intermediate results are pooled. The implementation allows fine-tuning.
☆142Updated last year
Alternatives and similar repositories for bert_for_longer_texts
Users that are interested in bert_for_longer_texts are comparing it to the libraries listed below
Sorting:
- Efficient Attention for Long Sequence Processing☆94Updated last year
- Comparing the Performance of LLMs: A Deep Dive into Roberta, Llama, and Mistral for Disaster Tweets Analysis with Lora☆51Updated last year
- ☆365Updated last year
- Code and experiments for *BERTopic: Neural topic modeling with a class-based TF-IDF procedure*☆77Updated last year
- Set of vectorizers that extract keyphrases with part-of-speech patterns from a collection of text documents and convert them into a docum…☆263Updated 7 months ago
- Creating class-based TF-IDF matrices☆84Updated 2 years ago
- ☆60Updated 4 years ago
- A repo to explore different NLP tasks which can be solved using T5☆172Updated 4 years ago
- ☆164Updated last year
- Text classification with Foundation Language Model LLaMA☆114Updated 2 years ago
- Use Large Language Models like OpenAI's GPT-3.5 for data annotation and model enhancement. This framework combines human expertise with L…☆38Updated last year
- Guideline following Large Language Model for Information Extraction☆380Updated 8 months ago
- Building NER and RE components using HuggingFace Transformers☆50Updated 3 years ago
- pyTorch implementation of Recurrence over BERT (RoBERT) based on this paper https://arxiv.org/abs/1910.10781 and comparison with pyTorch …☆82Updated 2 years ago
- Clustering sentence embeddings to extract message intent☆174Updated 3 years ago
- A Simple but Powerful SOTA NER Model | Official Code For Label Supervised LLaMA Finetuning☆155Updated last year
- Define Transformers, T5 model and RoBERTa Encoder decoder model for product names generation☆48Updated 3 years ago
- Full named-entity (i.e., not tag/token) evaluation metrics based on SemEval’13☆180Updated 2 weeks ago
- ☆52Updated 2 weeks ago
- Dense X Retrieval: What Retrieval Granularity Should We Use?☆157Updated last year
- A collection of topic diversity measures for topic modeling☆46Updated 3 years ago
- Language model fine-tuning on NER with an easy interface and cross-domain evaluation. "T-NER: An All-Round Python Library for Transformer…☆389Updated 2 years ago
- a library for named entity recognition developed by UF HOBI NLP lab featuring SOTA algorithms☆147Updated last year
- Zero and Few shot named entity & relationships recognition☆379Updated last month
- Fine-tuning of Flan-5T LLM for text classification 🤖 focuses on adapting a state-of-the-art language model to enhance its ability to cla…☆39Updated 8 months ago
- Instruct LLMs for flat and nested NER. Fine-tuning Llama and Mistral models for instruction named entity recognition. (Instruction NER)☆84Updated last year
- Resources for the "Evaluating the Factual Consistency of Abstractive Text Summarization" paper☆297Updated last month
- ☆66Updated 3 years ago
- A text truncation method, useful for instance in long text classification☆23Updated 3 years ago
- Data and models for the SciFact verification task.☆233Updated last year