#cplusplus #c_sharp #gamedev #multi_platform #game_engine #cpp #engine #game_development #flax #flax_engine #flaxengine
https://github.com/FlaxEngine/FlaxEngine
https://github.com/FlaxEngine/FlaxEngine
GitHub
GitHub - FlaxEngine/FlaxEngine: Flax Engine – multi-platform 3D game engine
Flax Engine – multi-platform 3D game engine. Contribute to FlaxEngine/FlaxEngine development by creating an account on GitHub.
#python #deep_learning #flax #jax #language_model #large_language_models #natural_language_processing #transformer
https://github.com/young-geng/EasyLM
https://github.com/young-geng/EasyLM
GitHub
GitHub - young-geng/EasyLM: Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning…
Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax. - young-geng/EasyLM
#python #bert #deep_learning #flax #hacktoberfest #jax #language_model #language_models #machine_learning #model_hub #natural_language_processing #nlp #nlp_library #pretrained_models #python #pytorch #pytorch_transformers #seq2seq #speech_recognition #tensorflow #transformer
The Hugging Face Transformers library provides thousands of pretrained models for various tasks like text, image, and audio processing. These models can be used for tasks such as text classification, image detection, speech recognition, and more. The library supports popular deep learning frameworks like JAX, PyTorch, and TensorFlow, making it easy to switch between them.
The benefit to the user is that you can quickly download and use these pretrained models with just a few lines of code, saving time and computational resources. You can also fine-tune these models on your own datasets and share them with the community. Additionally, the library offers a simple `pipeline` API for immediate use on different inputs, making it user-friendly for both researchers and practitioners. This helps in reducing compute costs and carbon footprint while enabling high-performance results across various machine learning tasks.
https://github.com/huggingface/transformers
The Hugging Face Transformers library provides thousands of pretrained models for various tasks like text, image, and audio processing. These models can be used for tasks such as text classification, image detection, speech recognition, and more. The library supports popular deep learning frameworks like JAX, PyTorch, and TensorFlow, making it easy to switch between them.
The benefit to the user is that you can quickly download and use these pretrained models with just a few lines of code, saving time and computational resources. You can also fine-tune these models on your own datasets and share them with the community. Additionally, the library offers a simple `pipeline` API for immediate use on different inputs, making it user-friendly for both researchers and practitioners. This helps in reducing compute costs and carbon footprint while enabling high-performance results across various machine learning tasks.
https://github.com/huggingface/transformers
GitHub
GitHub - huggingface/transformers: 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models…
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - GitHub - huggingface/t...
#python #deep_learning #diffusion #flax #flux #hacktoberfest #image_generation #image2image #image2video #jax #latent_diffusion_models #pytorch #score_based_generative_modeling #stable_diffusion #stable_diffusion_diffusers #text2image #text2video #video2video
The Hugging Face Diffusers library is a powerful and easy-to-use tool for generating images, audio, and 3D molecular structures using advanced diffusion models. It offers ready-to-use pretrained models and flexible components like pipelines, schedulers, and model building blocks, allowing you to quickly create or customize your own diffusion-based projects. Installation is simple via pip or conda, and you can generate high-quality outputs with just a few lines of code. This library benefits you by making cutting-edge AI generation accessible, customizable, and efficient, whether you want to run models or train your own[1][2][5].
https://github.com/huggingface/diffusers
The Hugging Face Diffusers library is a powerful and easy-to-use tool for generating images, audio, and 3D molecular structures using advanced diffusion models. It offers ready-to-use pretrained models and flexible components like pipelines, schedulers, and model building blocks, allowing you to quickly create or customize your own diffusion-based projects. Installation is simple via pip or conda, and you can generate high-quality outputs with just a few lines of code. This library benefits you by making cutting-edge AI generation accessible, customizable, and efficient, whether you want to run models or train your own[1][2][5].
https://github.com/huggingface/diffusers
GitHub
GitHub - huggingface/diffusers: 🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch. - huggingface/diffusers