torchmojiartifact
BentoML artifact framework for the Torchmoji Model.
Installation:
pip install torchmojiartifact==0.0.1
Usage example (decorate service):
from torchmojiartifact.TorchmojiModelArtifact import TorchmojiModelArtifact
@artifacts([TorchmojiModelArtifact('emojify')])
class MyBentoService(BentoService):
Usage example (package model):
svc = MyBentoService()
svc.pack('emojify', model_path)
Alternatively, during training:
svc.pack('emojify', {'state_dict': my_state_dict, 'emoji_list': my_emoji_list, 'pax_list': my_pax_list, 'vocabulary': my_vocab})
1 maintainer
Metadata
1 maintainer
Release files for torchmojiartifact 0.0.4
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| File | Size | Uploaded | Provenance | Actions |
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| torchmojiartifact-0.0.4.tar.gz | 2.4 kB | Without provenance | Details for torchmojiartifact-0.0.4.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| torchmojiartifact-0.0.4-py3-none-any.whl | Python 3 | none | any | Details for torchmojiartifact-0.0.4-py3-none-any.whl |
Total release size: 5.1 kB
Release files / torchmojiartifact-0.0.4.tar.gz
| Download URL | torchmojiartifact-0.0.4.tar.gz |
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| Size | 2.4 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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|
Release files / torchmojiartifact-0.0.4-py3-none-any.whl
| Download URL | torchmojiartifact-0.0.4-py3-none-any.whl |
|---|---|
| Size | 2.7 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.8.5
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