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    Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure

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  • 1
    Weights and Biases

    Weights and Biases

    Tool for visualizing and tracking your machine learning experiments

    ...Spend less time manually tracking results in spreadsheets and text files. Capture dataset versions with W&B Artifacts to identify how changing data affects your resulting models. Reproduce any model, with saved code, hyperparameters, launch commands, input data, and resulting model weights. Set wandb.config once at the beginning of your script to save your hyperparameters, input settings (like dataset name or model type), and any other independent variables for your experiments. This is useful for analyzing your experiments and reproducing your work in the future. Setting configs also allows you to visualize the relationships between features of your model architecture or data pipeline and model performance.
    Downloads: 5 This Week
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  • 2
    Transformer Reinforcement Learning X

    Transformer Reinforcement Learning X

    A repo for distributed training of language models with Reinforcement

    trlX is a distributed training framework designed from the ground up to focus on fine-tuning large language models with reinforcement learning using either a provided reward function or a reward-labeled dataset. Training support for Hugging Face models is provided by Accelerate-backed trainers, allowing users to fine-tune causal and T5-based language models of up to 20B parameters, such as facebook/opt-6.7b, EleutherAI/gpt-neox-20b, and google/flan-t5-xxl. For models beyond 20B parameters,...
    Downloads: 2 This Week
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