Showing 4 open source projects for "estimate"

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  • 1
    NBA Sports Betting Machine Learning

    NBA Sports Betting Machine Learning

    NBA sports betting using machine learning

    ...Using this dataset, the project constructs matchup features that represent team performance trends and contextual information about each game. Machine learning models are then trained to estimate the probability that a team will win a game as well as whether the total score will fall above or below the sportsbook’s predicted total. In addition to predicting outcomes, the project evaluates expected value to determine whether a potential bet offers a statistical advantage compared with sportsbook odds.
    Downloads: 2 This Week
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  • 2
    Gollama

    Gollama

    Go manage your Ollama models

    ...Beyond standard model management, Gollama can display metadata such as size, quantization level, model family, and modification date, which helps users compare models quickly. One of its more distinctive capabilities is a VRAM estimation system that can calculate memory requirements, estimate context limits, and help users choose quantization settings that fit available hardware.
    Downloads: 0 This Week
    Last Update:
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  • 3
    TokenCost

    TokenCost

    Easy token price estimates for 400+ LLMs. TokenOps

    TokenCost is an open-source developer utility designed to estimate the cost of using large language model APIs by calculating token usage and translating it into real monetary values. The tool focuses on helping developers understand how much their prompts and generated completions cost when interacting with commercial AI models. It works by counting tokens in prompts and responses before or after sending requests and then applying pricing information associated with different models. ...
    Downloads: 0 This Week
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  • 4
    gpu_poor

    gpu_poor

    Calculate token/s & GPU memory requirement for any LLM

    gpu_poor is an open-source tool designed to help developers determine whether their hardware is capable of running a specific large language model and to estimate the performance they can expect from it. The project focuses on calculating GPU memory requirements and predicted inference speed for different models, hardware configurations, and quantization strategies. By analyzing factors such as model size, context length, batch size, and GPU specifications, the system estimates how much VRAM will be required and how fast tokens can be generated during inference. ...
    Downloads: 0 This Week
    Last Update:
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