This is the Windows app named LLaMA Models whose latest release can be downloaded as v0.2.0sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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- 7. Muat turun Wine dari repositori perisian pengedaran Linux anda. Setelah dipasang, anda kemudian boleh mengklik dua kali aplikasi untuk menjalankannya dengan Wine. Anda juga boleh mencuba PlayOnLinux, antara muka mewah melalui Wine yang akan membantu anda memasang program dan permainan Windows yang popular.
Wain ialah cara untuk menjalankan perisian Windows pada Linux, tetapi tanpa Windows diperlukan. Wain ialah lapisan keserasian Windows sumber terbuka yang boleh menjalankan program Windows secara langsung pada mana-mana desktop Linux. Pada asasnya, Wine cuba untuk melaksanakan semula Windows yang mencukupi dari awal supaya ia boleh menjalankan semua aplikasi Windows tersebut tanpa memerlukan Windows.
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LLaMA Models
DESCRIPTION
This repository serves as the central hub for the Llama foundation model family, consolidating model cards, licenses and use policies, and utilities that support inference and fine-tuning across releases. It ties together other stack components (like safety tooling and developer SDKs) and provides canonical references for model variants and their intended usage. The project’s issues and releases reflect an actively used coordination point for the ecosystem, where guidance, utilities, and compatibility notes are published. It complements separate repos that carry code and demos (for example inference kernels or cookbook content) by keeping authoritative metadata and specs here. Model lineages and size variants are documented externally (e.g., Llama 3.x and beyond), with this repo providing the “single source of truth” links and utilities. In practice, teams use llama-models as a reference when selecting variants, aligning licenses, and wiring in helper scripts for deployment.
Ciri-ciri
- Centralized model cards and licensing information
- Utilities and reference scripts for Llama models
- Canonical pointers to inference and fine-tuning stacks
- Ecosystem coordination via issues and documentation
- Compatibility notes across Llama releases and variants
- Source of truth for policies and usage guidance
Bahasa Pengaturcaraan
Python
Kategori
This is an application that can also be fetched from https://sourceforge.net/projects/llama-models.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.