LSTP-Chat: Language-guided Spatial-Temporal Prompt Learning for Video Chat
Available Models:
LSTP-Chat-7B (Vicuna-7b)
For more details, please refer to our official repository
Source link
ACHVR AI
College Profile National Institute of Technology, Warangal (Deemed University) , formerly known as Regional Engineering College, was established in 1959. The Institute currently has thirteen academic departments and a few advanced research centres in various disciplines of engineering, pure sciences and management, with nearly 100 laboratories organized in a unique pattern of functioning, Central Library with state…
frizwankhan/entity-linking-model-final
Document Question Answering
•
Updated
Jan 13, 2022
•
71
Source link
As fake nudes become latest AI headache, experts call for regulation and awareness | Technology News
The small Spanish town of Almendralejo was shaken when dozens of schoolgirls reported that their nude images, generated using an “undress” app employing Artificial Intelligence, were circulated and shared on everyone’s phones at school.
In another case, a high school in New Jersey made headlines when a high schooler made deepfake pornographic images of his female…
Vision-and-Language Transformer (ViLT), fine-tuned on VQAv2
Vision-and-Language Transformer (ViLT) model fine-tuned on VQAv2. It was introduced in the paper ViLT: Vision-and-Language Transformer
Without Convolution or Region Supervision by Kim et al. and first released in this repository.
Disclaimer: The team releasing ViLT did not write a model card for this model so this model…
Depth Anything (small-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. and first released in this repository.
Online demo is also provided.
Disclaimer: The team releasing Depth Anything did not write a model card for this…
Edit model card
Vision Transformer (base-sized model)
Model description
Intended uses & limitations
How to use
Training data
Training procedure
Preprocessing
Pretraining
Evaluation results
BibTeX entry and citation info
Vision Transformer (base-sized model)
Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224, and fine-tuned on ImageNet 2012…
Edit model card
Q-Learning Agent playing1 FrozenLake-v1
Usage
Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
Usage
model = load_from_hub(repo_id="alperenunlu/q-FrozenLake-v1-4x4-noSlippery" , filename="q-learning.pkl" )
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id" ])
…