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T5Gemma conversion and inference - #1962
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Thanks for your quick work on this! This looks good in my brief testing. Conversion and inference both appear to function as intended. I tested using t5gemma-s-s-prefixlm-it. The following input: [
"<start_of_turn>", "user", "\n",
"What", "▁is", "▁the", "▁capital", "▁of", "▁France", "?", "<end_of_turn>", "\n",
"<start_of_turn>", "model", "\n"
]Correctly produces this output: [
"The", "▁capital", "▁of", "▁France", "▁is", "▁**", "Paris", "**.", "▁", "\n"
] |
a2d8a4v
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Jan 13, 2026
See OpenNMT#1946 Changes: - Support for T5Gemma family models - Extract qk_norm logic to its own method - Add support for rotary embeddings and pre and post layers in encoder - Support for different types of cross attention and unit tests
Lanurence666
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May 23, 2026
See OpenNMT#1946 Changes: - Support for T5Gemma family models - Extract qk_norm logic to its own method - Add support for rotary embeddings and pre and post layers in encoder - Support for different types of cross attention and unit tests
veilnetwork
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See OpenNMT#1946 Changes: - Support for T5Gemma family models - Extract qk_norm logic to its own method - Add support for rotary embeddings and pre and post layers in encoder - Support for different types of cross attention and unit tests
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See #1946
Python wheels are available to test here:
https://github.com/OpenNMT/CTranslate2/actions/runs/20646214823#artifacts
Changes: