mattshumer/Reflection-Llama-3.1-70B · Hugging Face
Reflection Llama-3.1 70B | IMPORTANT UPDATE – There was an issue with the model when we first uploaded it. If you tried it and didn't have good results, please, try again, we think we've fixed the issue. Reflection Llama-3.1 70B is (currently) the world's top open-source LLM, trained with a new technique called Reflection-Tuning that teaches a LLM to detect mistakes in its reasoning and correct co
Qwen/Qwen2-VL-2B-Instruct · Hugging Face
Requirements The code of Qwen2-VL has been in the latest Hugging face transformers and we advise you to build from source with command pip install git+https://github.com/huggingface/transformers, or you might encounter the following error: KeyError: 'qwen2_vl' Quickstart We offer a toolkit to help you handle various types of visual input more conveniently. This includes base64, URLs, and interleav
Mozilla/whisperfile · Hugging Face
OpenAI Whisper - llamafile Whisperfile is a high-performance implementation of OpenAI's Whisper created by Mozilla Ocho as part of the llamafile project, based on the whisper.cpp software written by Georgi Gerganov, et al. Model creator: OpenAI Original models: openai/whisper-release Origin of quantized weights: ggerganov/whisper.cpp The model is packaged into executable weights, which we call whi
microsoft/Phi-3.5-vision-instruct · Hugging Face
Model Summary Phi-3.5-vision is a lightweight, state-of-the-art open multimodal model built upon datasets which include - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data both on text and vision. The model belongs to the Phi-3 model family, and the multimodal version comes with 128K context length (in tokens) it can support. The mode
Introducing TextImage Augmentation for Document Images
Introducing Multimodal TextImage Augmentation for Document Images In this blog post, we provide a tutorial on how to use a new data augmentation technique for document images, developed in collaboration with Albumentations AI. Motivation Vision Language Models (VLMs) have an immense range of applications, but they often need to be fine-tuned to specific use-cases, particularly for datasets contain
vidore/colpali · Hugging Face
ColPali: Visual Retriever based on PaliGemma-3B with ColBERT strategy ColPali is a model based on a novel model architecture and training strategy based on Vision Language Models (VLMs) to efficiently index documents from their visual features. It is a PaliGemma-3B extension that generates ColBERT- style multi-vector representations of text and images. It was introduced in the paper ColPali: Effic
Perplexity of fixed-length models
Perplexity (PPL) is one of the most common metrics for evaluating language models. Before diving in, we should note that the metric applies specifically to classical language models (sometimes called autoregressive or causal language models) and is not well defined for masked language models like BERT (see summary of the models). Perplexity is defined as the exponentiated average negative log-like
teknium/OpenHermes-2.5 · Datasets at Hugging Face
2048 Token Examples":1,"Collaboration for Effective Communication.":1,"Taco Seasoning Recipe":1,"Invite collaborator privately.":1,"提高自律能力":1,"Stinky Doge Coin Rap":1,"エクセル：文字列の結合 (Excel: Concatenating Strings)":1}}}},{"name":"topic","align":"right","type":"null","statistics":{"column_name":"topic","column_type":"string_label","column_statistics":{"nan_count":1000891,"nan_proportion":0.99934,"no_l
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mattshumer/Reflection-Llama-3.1-70B · Hugging Face
microsoft/mocapact-data · Datasets at Hugging Face
ThePioneer/japanese-photos · Datasets at Hugging Face
internlm/internlm2-step-prover · Hugging Face
https://huggingface.co/datasets/mlfoundations/MINT-1T-ArXiv
mlfoundations/MINT-1T-PDF-CC-2024-18 · Datasets at Hugging Face
mlfoundations/MINT-1T-HTML · Datasets at Hugging Face
TrOCR
microsoft/llava-med-v1.5-mistral-7b · Hugging Face
CohereForAI/aya-23-8B · Hugging Face
WizardLMTeam (WizardLM Team)
m-a-p/CodeFeedback-Filtered-Instruction · Datasets at Hugging Face