Showing 254 open source projects for "pyscripter python 2"

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    whisper-large-v3-turbo

    whisper-large-v3-turbo

    Whisper-large-v3-turbo delivers fast, multilingual speech recognition

    ..., temperature fallback, and timestamp prediction. Whisper-large-v3-turbo works with long-form and real-time audio, with chunked or sequential inference options. Optimizations such as torch.compile, Flash Attention 2, and SDPA are available to enhance performance. Despite being smaller than v3, it retains strong robustness to accents, noise, and zero-shot tasks, making it ideal for scalable, multilingual ASR use cases.
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  • 2
    OpenVLA 7B

    OpenVLA 7B

    Vision-language-action model for robot control via images and text

    ... supports real-world robotics tasks, with robust generalization to environments seen in pretraining. Its actions include delta values for position, orientation, and gripper status, and can be un-normalized based on robot-specific statistics. OpenVLA is MIT-licensed, fully open-source, and designed collaboratively by Stanford, Berkeley, Google DeepMind, and TRI. Deployment is facilitated via Python and Hugging Face tools, with flash attention support for efficient inference.
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  • 3
    Monk Computer Vision

    Monk Computer Vision

    A low code unified framework for computer vision and deep learning

    Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms. - Monk Object Detection -...
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  • 4
     stable-diffusion-v1-4

    stable-diffusion-v1-4

    Text-to-image diffusion model for high-quality image generation

    stable-diffusion-v1-4 is a high-performance text-to-image latent diffusion model developed by CompVis. It generates photo-realistic images from natural language prompts using a pretrained CLIP ViT-L/14 text encoder and a UNet-based denoising architecture. This version builds on v1-2, fine-tuned over 225,000 steps at 512×512 resolution on the “laion-aesthetics v2 5+” dataset, with 10% text-conditioning dropout for improved classifier-free guidance. It is optimized for use with Hugging Face’s...
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