Transformer-based models to fast-simulate the LHCb ECAL detector
Project description
Transformer-based models to fast-simulate the LHCb ECAL detector
Credits
Transformer implementation freely inspired by the TensorFlow tutorial Neural machine translation with a Transformer and Keras.
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
calotron-0.0.11.tar.gz
(33.8 kB
view details)
Built Distribution
calotron-0.0.11-py3-none-any.whl
(49.8 kB
view details)
File details
Details for the file calotron-0.0.11.tar.gz.
File metadata
- Download URL: calotron-0.0.11.tar.gz
- Upload date:
- Size: 33.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.15
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 105e853a53590a5be38e7874ccd03ddc65bf851a9af5360e01806579ba8620a3 |
|
| MD5 | 71421b82de49d709fc16e199f5bb2dcc |
|
| BLAKE2b-256 | a9765553190e110afaa37918d75e8277e99a24826fc9b4c8cebd896f1532fa58 |
File details
Details for the file calotron-0.0.11-py3-none-any.whl.
File metadata
- Download URL: calotron-0.0.11-py3-none-any.whl
- Upload date:
- Size: 49.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.15
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 252d4aa0cc6271dc5007c16fca024c947c91e62d110ed2f0b427e47e0ab1c3fa |
|
| MD5 | c8e7ffa4c43838c918eefdfb17d4b00e |
|
| BLAKE2b-256 | 89775efd3957111bc65ee6016704a56ef2d7ef34340ecbad14a73fd1b9770e9f |
