This is the Windows app named fairseq2 whose latest release can be downloaded as v0.5.2sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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- 7. I-download ang Wine mula sa iyong mga Linux distributions software repository. Kapag na-install na, maaari mong i-double click ang app upang patakbuhin ang mga ito gamit ang Wine. Maaari mo ring subukan ang PlayOnLinux, isang magarbong interface sa ibabaw ng Wine na tutulong sa iyong mag-install ng mga sikat na programa at laro sa Windows.
Ang alak ay isang paraan upang patakbuhin ang software ng Windows sa Linux, ngunit walang kinakailangang Windows. Ang alak ay isang open-source na layer ng compatibility ng Windows na maaaring direktang magpatakbo ng mga program sa Windows sa anumang desktop ng Linux. Sa totoo lang, sinusubukan ng Wine na muling ipatupad ang sapat na Windows mula sa simula upang mapatakbo nito ang lahat ng mga Windows application na iyon nang hindi talaga nangangailangan ng Windows.
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fairseq2
DESCRIPTION
fairseq2 is a modern, modular sequence modeling framework developed by Meta AI Research as a complete redesign of the original fairseq library. Built from the ground up for scalability, composability, and research flexibility, fairseq2 supports a broad range of language, speech, and multimodal content generation tasks, including instruction fine-tuning, reinforcement learning from human feedback (RLHF), and large-scale multilingual modeling. Unlike the original fairseq—which evolved into a large, monolithic codebase—fairseq2 introduces a clean, plugin-oriented architecture designed for long-term maintainability and rapid experimentation. It supports multi-GPU and multi-node distributed training using DDP, FSDP, and tensor parallelism, capable of scaling up to 70B+ parameter models. The framework integrates seamlessly with PyTorch 2.x features such as torch.compile, Fully Sharded Data Parallel (FSDP), and modern configuration management.
Mga tampok
- Composable and deterministic configuration system
- High-throughput C++ streaming data pipeline for text and speech
- Recipes for instruction fine-tuning, preference optimization, and RLHF
- Native vLLM integration for optimized generation and inference
- Supports 70B+ parameter models with DDP, FSDP, and tensor parallelism
- Modular, next-generation fairseq with a clean, extensible architecture
Wika ng Programming
C, C++, Python, Unix Shell
Kategorya
This is an application that can also be fetched from https://sourceforge.net/projects/fairseq2.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
