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AI: AI, High Performance Computing Research Centre opened at IIT Bhubaneswar | Bhubaneswar News

BHUBANESHWAR: To conduct interdisciplinary and collaborative research in the fields of artificial intelligence (AI) and high performance computing (HPC), the IIT Bhubaneswar has established a new AI and HPC Research Center (AHRC) in its campus. The institution has designed it as a national research center with participation of other noted academic, industry and government research…
March 6, 20240Likes0Comments
AI News

Vivo siphoned $13 bn abroad, ED tells court

Many employees of Chinese smartphone maker Vivo and its Indian affiliates concealed their employment when seeking visas, and some breached rules by visiting the “sensitive" Himalayan region of Jammu and Kashmir, India’s financial crime agency has said. The court statement comes as tension rises with Beijing over business activities after New Delhi tightened curbs on incoming…
March 6, 20240Likes0Comments
Text Classification

bert-base-personality

How to Get Started with the Model To use the model through Hosted inference API, follow the code snippet provided below: from transformers import BertTokenizer, BertForSequenceClassification def personality_detection (text ): tokenizer = BertTokenizer.from_pretrained("Minej/bert-base-personality" ) model = BertForSequenceClassification.from_pretrained("Minej/bert-base-personality" ) inputs = tokenizer(text, truncation=True ,…
March 6, 20240Likes0Comments
VLLMs

udop-large

UDOP model The UDOP model was proposed in Unifying Vision, Text, and Layout for Universal Document Processing by Zineng Tang, Ziyi Yang, Guoxin Wang, Yuwei Fang, Yang Liu, Chenguang Zhu, Michael Zeng, Cha Zhang, Mohit Bansal. Model description UDOP adopts an encoder-decoder Transformer architecture based on T5 for document AI tasks like…
March 5, 20240Likes0Comments
Document Question Answering

layoutlmv3-base-mpdocvqa

LayoutLMv3 base fine-tuned on MP-DocVQA This is pretrained LayoutLMv3 from Microsoft hub and fine-tuned on Multipage DocVQA (MP-DocVQA) dataset. This model was used as a baseline in Hierarchical multimodal transformers for Multi-Page DocVQA. Results on the MP-DocVQA dataset are reported in Table 2. Training hyperparameters can be found in Table 8 of Appendix D.…
March 5, 20240Likes0Comments
Visual Question Answering

git-large-vqav2

GIT (GenerativeImage2Text), large-sized, fine-tuned on VQAv2 GIT (short for GenerativeImage2Text) model, large-sized version, fine-tuned on VQAv2. It was introduced in the paper GIT: A Generative Image-to-text Transformer for Vision and Language by Wang et al. and first released in this repository. Disclaimer: The team releasing GIT did not write a model card for this…
March 5, 20240Likes0Comments
Depth Estimation

lap-depth-kitti-grad

LapDepth-release This repository is a Pytorch implementation of the paper "Monocular Depth Estimation Using Laplacian Pyramid-Based Depth Residuals" Minsoo Song, Seokjae Lim, and Wonjun Kim* IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) Official Repository: LapDepth-release License: GPL-3.0 license Usage from model import…
March 5, 20240Likes0Comments