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bump 3.5 (#2565)
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CHANGELOG.md

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## [Unreleased]
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## [3.5.0](https://github.com/OpenNMT/OpenNMT-py/tree/3.5.0) (2024-02-22)
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* Further improvements and fixes
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* Suport for AWQ models
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* Add n_best for topp/topk generation
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* Support MoE (MIxtral) inference
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* Extend HF models converter
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* use flash_attn_with_kvcache for faster inference
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* Add wikitext2 PPL computation
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* Support for Phi-2 models
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## [3.4.3](https://github.com/OpenNMT/OpenNMT-py/tree/3.4.3) (2023-11-2)
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* Further improvements to beam search and decoding

README.md

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----
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## New:
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* You will need Pytorch v2 preferably v2.1 which fixes some `scaled_dot_product_attention` issues
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* You will need Pytorch v2 preferably v2.2 which fixes some `scaled_dot_product_attention` issues
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* LLM support with converters for: Llama (+ Mistral), OpenLlama, Redpajama, MPT-7B, Falcon.
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* Support for 8bit and 4bit quantization along with LoRA adapters, with or without checkpointing.
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* You can finetune 7B and 13B models on a single RTX 24GB with 4-bit quantization.

onmt/__init__.py

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onmt.modules,
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]
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__version__ = "3.4.3"
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__version__ = "3.5.0"

setup.py

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description="A python implementation of OpenNMT",
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long_description=long_description,
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long_description_content_type="text/markdown",
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version="3.4.3",
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version="3.5.0",
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packages=find_packages(),
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project_urls={
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"Documentation": "http://opennmt.net/OpenNMT-py/",
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},
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python_requires=">=3.8",
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install_requires=[
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"torch>=2.0.1,<2.2",
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"torch>=2.0.1,<2.3",
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"configargparse",
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"ctranslate2>=3.17,<4",
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"ctranslate2>=3.24,<5",
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"tensorboard>=2.3",
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"flask",
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"waitress",

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