Depth Anything model, small
The model card for our paper Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data.
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SeamlessStreaming
SeamlessStreaming models
Evaluating SeamlessStreaming models
Seamless Streaming demo
Running on HF spaces
Running locally
Install backend seamless_server dependencies
Install frontend streaming-react-app dependencies
Running the server
Debuging
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Twitter-roBERTa-base for Sentiment Analysis - UPDATED (2022)
This is a RoBERTa-base model trained on ~124M tweets from January 2018 to December 2021, and finetuned for sentiment analysis with the…
TinyLLaVA: A Framework of Small-scale Large Multimodal Models
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[2024.02.25] Update evaluation scripts and docs!
[2024.02.25] Data descriptions out. Release…
Model card for Pix2Struct - Finetuned on Doc-VQA (Visual Question Answering over scanned documents) - large version
Table of Contents
TL;DR
Using the model
Contribution
Citation…
Depth Anything (base-sized model, Transformers version)
Depth Anything model. It was introduced in the paper Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data by Lihe Yang et al.…
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BCEmbedding: Bilingual and Crosslingual Embedding for RAG
最新、最详细bce-reranker-base_v1相关信息，请移步（The latest "Updates" should be checked…