This is the Linux app named Gemma in PyTorch whose latest release can be downloaded as gemma_pytorchsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Gemma in PyTorch with OnWorks for free.
Volg deze instructies om deze app uit te voeren:
- 1. Download deze applicatie op uw pc.
- 2. Voer in onze bestandsbeheerder https://www.onworks.net/myfiles.php?username=XXXXX in met de gebruikersnaam die u wilt.
- 3. Upload deze applicatie in zo'n bestandsbeheerder.
- 4. Start de OnWorks Linux online of Windows online emulator of MACOS online emulator vanaf deze website.
- 5. Ga vanuit het OnWorks Linux-besturingssysteem dat u zojuist hebt gestart naar onze bestandsbeheerder https://www.onworks.net/myfiles.php?username=XXXXX met de gewenste gebruikersnaam.
- 6. Download de applicatie, installeer hem en voer hem uit.
SCREENSHOTS
Ad
Gemma in PyTorch
PRODUCTBESCHRIJVING
gemma_pytorch provides the official PyTorch reference for running and fine-tuning Google’s Gemma family of open models. It includes model definitions, configuration files, and loading utilities for multiple parameter scales, enabling quick evaluation and downstream adaptation. The repository demonstrates text generation pipelines, tokenizer setup, quantization paths, and adapters for low-rank or parameter-efficient fine-tuning. Example notebooks walk through instruction tuning and evaluation so teams can benchmark and iterate rapidly. The code is organized to be legible and hackable, exposing attention blocks, positional encodings, and head configurations. With standard PyTorch abstractions, it integrates easily into existing training loops, loggers, and evaluation harnesses.
Kenmerken
- PyTorch implementations and configs for Gemma model variants
- Ready-to-use generation, tokenization, and checkpoint loading
- Drop-in modules compatible with common PyTorch stacks
- Example notebooks for tuning and evaluation
- Quantization and inference optimization paths
- Parameter-efficient fine-tuning adapters and examples
Programmeertaal
Python
Categorieën
This is an application that can also be fetched from https://sourceforge.net/projects/gemma-in-pytorch.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
