vima - Pytorch
Project description
VIM
A simple implementation of "VIMA: General Robot Manipulation with Multimodal Prompts"
Appreciation
- Lucidrains
- Agorians
Install
pip install vima
Usage
import torch
from vima import Vima
# Generate a random input sequence
x = torch.randint(0, 256, (1, 1024)).cuda()
# Initialize VIMA model
model = Vima()
# Pass the input sequence through the model
output = model(x)
MultiModal Iteration
- Pass in text and and image tensors into vima
import torch
from vima.vima import VimaMultiModal
#usage
img = torch.randn(1, 3, 256, 256)
text = torch.randint(0, 20000, (1, 1024))
model = VimaMultiModal()
output = model(text, img)
License
MIT
Citations
@inproceedings{jiang2023vima,
title = {VIMA: General Robot Manipulation with Multimodal Prompts},
author = {Yunfan Jiang and Agrim Gupta and Zichen Zhang and Guanzhi Wang and Yongqiang Dou and Yanjun Chen and Li Fei-Fei and Anima Anandkumar and Yuke Zhu and Linxi Fan},
booktitle = {Fortieth International Conference on Machine Learning},
year = {2023}
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
vima-0.0.2.tar.gz
(25.3 kB
view details)
Built Distribution
vima-0.0.2-py3-none-any.whl
(26.3 kB
view details)
File details
Details for the file vima-0.0.2.tar.gz
.
File metadata
- Download URL: vima-0.0.2.tar.gz
- Upload date:
- Size: 25.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.3.2 CPython/3.11.0 Darwin/22.4.0
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | eb458c3f26586668547962bb0ad031fa63475f62f783682ef84416b279829bf8 |
|
MD5 | 6408b8791ad9d7bf4a9b8b5875463e2e |
|
BLAKE2b-256 | a3496f37fd63826ab028595f674257eef6a88aec0f8e2b1ebabe6319a2e86dab |
File details
Details for the file vima-0.0.2-py3-none-any.whl
.
File metadata
- Download URL: vima-0.0.2-py3-none-any.whl
- Upload date:
- Size: 26.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.3.2 CPython/3.11.0 Darwin/22.4.0
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8e2ba3a331d7566a043aea4c1ac5ceb6a54a2e141bc6c4049214c030ca6a26ee |
|
MD5 | 3798275df741489b8684864127629c98 |
|
BLAKE2b-256 | 0610e7d1f2d201507e3e9d09a1d488d31b4125fc2384955e996fc04ab021c411 |