GitHub - MaartenGr/KeyBERT: Minimal keyword extraction with BERT

GitHub - arthur-ai/bench: A tool for evaluating LLMs

Text embeddings are a critical piece of many pipelines, from search, to RAG, to vector databases and more. Most embedding models are BERT/Transformer-based and typically have short context lengths (e.g., 512). That’s only about two pages of text, but documents can be very long – books, legal cases, TV screenplays, code repositories, etc can be tens... See more

1. Introduction of DeepSeek Coder

DeepSeek Coder is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language in both English and Chinese. We provide various sizes of the code model, ranging from 1B to 33B versions. Each model is pre-trained on project-level code co... See more

Pretrained model on protein sequences using a masked language modeling (MLM) objective. It was introduced in

this paper and first released in

this repository. This model is trained on uppercase amino acids: it only works with capital letter amino acids.

Model description

ProtBert is based on Bert model which pretrained on a large corpus of protein sequ... See more

I used this system to design self-documenting components that were easy to develop against, and allowed the rest of the team to build new and consistent UI without needing me.

- Leveraging Document and Corpus Structure-  Scaling to Multiple Languages]

ColBERT is a

fast

and

accurate

retrieval model, enabling scalable BERT-based search over large text collections in tens of milliseconds.

Figure 1: ColBERT's late interaction, efficiently scoring the fine-grained similarity between a queries and a passage.

As Figure 1 illustrates, ColBERT relies on fine-grained contextual late interaction : it encod... See more

𝗺𝗲𝘁𝗵𝗼𝗱𝘀 𝗼𝗳 𝗳𝗶𝗻𝗲-𝘁𝘂𝗻𝗶𝗻𝗴 𝗮𝗻 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲 𝗟𝗟𝗠 𝗲𝘅𝗶𝘀t ↓

- 𝘊𝘰𝘯𝘵𝘪𝘯𝘶𝘦𝘥 𝘱𝘳𝘦-𝘵𝘳𝘢𝘪𝘯𝘪𝘯𝘨: utilize domain-specific data to apply the same pre-training process (next token prediction) on the pre-trained (base) model

- 𝘐𝘯𝘴𝘵𝘳𝘶𝘤𝘵𝘪𝘰𝘯 𝘧𝘪𝘯𝘦-𝘵𝘶𝘯𝘪𝘯𝘨: the pre-trained (base) model is fine-tuned on ... See more