recurrent-memory-transformer-pytorch 0.7.0
pip install recurrent-memory-transformer-pytorch
Latest version
Released:
Recurrent Memory Transformer - Pytorch
Navigation
Unverified details
These details have not been verified by PyPIProject links
Meta
- License: MIT License (MIT)
- Author: Phil Wang
- Tags artificial intelligence, deep learning, transformers, attention mechanism, recurrence, memory, long-context
Classifiers
- Development Status
- Intended Audience
- License
- Programming Language
- Topic
Project description
The author of this package has not provided a project description
Project details
Unverified details
These details have not been verified by PyPIProject links
Meta
- License: MIT License (MIT)
- Author: Phil Wang
- Tags artificial intelligence, deep learning, transformers, attention mechanism, recurrence, memory, long-context
Classifiers
- Development Status
- Intended Audience
- License
- Programming Language
- Topic
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
Built Distribution
recurrent_memory_transformer_pytorch-0.7.0-py3-none-any.whl
(10.8 kB
view details)
Uploaded
Python 3
File details
Details for the file recurrent_memory_transformer_pytorch-0.7.0.tar.gz
.
File metadata
- Download URL: recurrent_memory_transformer_pytorch-0.7.0.tar.gz
- Upload date:
- Size: 13.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.9.21
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | b9550b45074a7ab31c45cb9d33131a7dcd04074c4dfdefc1550353dff5eaf23c |
|
MD5 | 8d29467d456fad5c7f7aa447094a806d |
|
BLAKE2b-256 | 11066c9b1fd262e1ffddec5b26454aafc26652008f9acdf6408321b77ae846ec |
File details
Details for the file recurrent_memory_transformer_pytorch-0.7.0-py3-none-any.whl
.
File metadata
- Download URL: recurrent_memory_transformer_pytorch-0.7.0-py3-none-any.whl
- Upload date:
- Size: 10.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.9.21
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7a023c43223520b1cef85ca31e51f61978ef599c631deb9b8f154f737b57c3b2 |
|
MD5 | 63819b7afa955e56139afb378be9ed24 |
|
BLAKE2b-256 | 045085bda8cf5ce4060bb681ede41562ec6c3582d50aff2e03b483cbee0ba0d6 |