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bge-reranker-large

FlagEmbedding Model List | FAQ | Usage | Evaluation | Train | Contact | Citation | License More details please refer to our Github: FlagEmbedding. English | 中文 FlagEmbedding focuses on retrieval-augmented LLMs, consisting of the following projects currently: Long-Context LLM: Activation Beacon Fine-tuning of LM : LM-Cocktail Dense Retrieval: BGE-M3, LLM Embedder, BGE Embedding Reranker Model: BGE Reranker Benchmark: C-MTEB  …

llava-1.6-gguf

Update: PR is merged, llama.cpp now natively supports these models Important: Verify that processing a simple question with any image at least uses 1200 tokens of prompt processing, that shows that the new PR is in use. If your prompt is just 576 + a few tokens, you are using llava-1.5 code (or projector) and this…

layoutlm-document-qa

LayoutLM for Visual Question Answering This is a fine-tuned version of the multi-modal LayoutLM model for the task of question answering on documents. It has been fine-tuned using both the SQuAD2.0 and DocVQA datasets. Getting started with the model To run these examples, you must have PIL, pytesseract, and PyTorch installed in…

tinyllava-1.1b-v0.1

About This was trained by using TinyLlama as the base model using the BakLlava repo. Examples Prompt for both was, "What is shown in the given image?" Install If you are not using Linux, do NOT proceed, see instructions for macOS and Windows. Clone this repository and navigate to…

Creator’s Guide to How to Write Smile Captions for Instagram to Deepen Your Audience Affinity

Ah, smile captions. 🙂  If you’re a creator or influencer on the hunt for memorable smile captions for Instagram, you’re not alone. There are hundreds of lists of famous quotes and heartwarming platitudes out there. But here’s the thing…that’s not the best way to go about captioning your selfie. The problem with copy-paste smile captions…