Comments (2)
Hi @dblandan I released version 1.2.0 but just for a few hours and then decided to roll-back. We want to release new default
models but we want to avoid confusion and people reporting scores that are not comparable with previous versions. To avoid that I need to finish documentation on new models first.
Sorry by the confusion! Also, entmax was breaking the install and I asked Ben Peters if they could bump entmax, I see that it was fixed already!
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There's a workaround, of course:
pip install -e git+https://github.com/Unbabel/[email protected]#egg=unbabel-comet
but it would be nice if the latest version were in the registry.
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Related Issues (20)
- [QUESTION] Train UnifiedMetric/XCOMET with word level predictions. HOT 1
- Sparsemax not actually used in COMET-KIWI, XCOMET-XL/XXL HOT 4
- Invalid link reference of reference-free model in readme
- Minimizing cpu RAM vs only use GPU RAM HOT 1
- what is the precision when load_from_checkpoint?
- Runtime error when loading wmt23-cometkiwi-da-xl HOT 1
- Different scores from different COMET package versions 1.1.2 and 2.2.1 HOT 2
- Different versions of COMET code give different scores with the same model and date.
- [QUESTION] large file scoring HOT 3
- [QUESTION] Splitting big models over multiple GPUs HOT 6
- [QUESTION] Memory footprint HOT 21
- [INPUT] Text Length of Input (source, reference, and hypothesis) HOT 2
- Change the global variable logger to comet_logger HOT 1
- Training script for XCOMET HOT 1
- Safetensors Support
- [QUESTION] OOM when load XCOMET-XXL in A100 with 40G memory for prediction HOT 4
- [QUESTION] why num_layers = num_hidden_layers + 1 HOT 1
- [QUESTION] Comet kiwi architecture HOT 11
- Training data and scripts used for wmt22-cometkiwi-da HOT 4
- Add missing library stubs or py.typed marker
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