#cplusplus #artificial_intelligence #autograd #convolutional_neural_network #generative_adversarial_network #language_model #libtorch #machine_learning #neural_network #pytorch #recurrent_neural_network #tensors #torch #tutorial

https://github.com/prabhuomkar/pytorch-cpp

#python #gpt #gpt_2 #gpt_3 #language_model #transformers

https://github.com/EleutherAI/gpt-neo

#python #text_classification #text #transformer #vision #image_classification #feedforward_neural_network #language_model #fourier_transform #fnet

https://github.com/rishikksh20/FNet-pytorch

#python #ai #bert #dpr #elasticsearch #information_retrieval #language_model #machine_learning #natural_language_processing #neural_search #nlp #pytorch #question_answering #search_engine #semantic_search #squad #summarization #transfer_learning #transformers

https://github.com/deepset-ai/haystack

#python #callcenter #conformer #ctc_decode #deepspeech #fastspeech2 #language_model #mandarin_language #ngram #parallel_wavegan #punctuation_restoration #speech_alignment #speech_recognition #speech_to_text #speech_translation #streaming_asr #text_frontend #text_to_speech #transformer

https://github.com/PaddlePaddle/PaddleSpeech

#python #computer_vision #contrastive_loss #deep_learning #language_model #multi_modal_learning #pretrained_models #pytorch #zero_shot_classification

https://github.com/mlfoundations/open_clip

#python #bert #deep_learning #language_model #language_models #machine_learning #natural_language_processing #nlp #pytorch #transformer

https://github.com/extreme-bert/extreme-bert

#python #attention_mechanism #deep_learning #gpt #gpt_2 #gpt_3 #language_model #linear_attention #lstm #pytorch #rnn #rwkv #transformer #transformers

https://github.com/BlinkDL/RWKV-LM

#python #deepspeed_library #gpt_3 #language_model #transformers

https://github.com/EleutherAI/gpt-neox

#python #agi #gpt #language_model #llm #lm #lmops #nlp #pretraining #prompt #promptist #x_prompt

https://github.com/microsoft/LMOps

#python #deep_learning #flax #jax #language_model #large_language_models #natural_language_processing #transformer

https://github.com/young-geng/EasyLM

#python #embeddings #information_retrieval #language_model #large_language_models #llm #machine_learning #nearest_neighbor_search #neural_search #nlp #search #search_engine #semantic_search #sentence_embeddings #similarity_search #transformers #txtai #vector_database #vector_search #vector_search_engine

https://github.com/neuml/txtai

#jupyter_notebook #ai #azure #chatgpt #dall_e #generative_ai #generativeai #gpt #language_model #llms #openai #prompt_engineering #semantic_search #transformers

This course teaches you how to build Generative AI applications with 21 comprehensive lessons from Microsoft Cloud Advocates. You'll learn about Generative AI, Large Language Models (LLMs), prompt engineering, and how to build various applications like text generation, chat apps, and image generation using Python and TypeScript. The course includes videos, written lessons, code samples, and additional learning resources. You can start anywhere and even join a Discord server for support and networking with other learners. This helps you gain practical skills in building and deploying Generative AI applications responsibly and effectively.

https://github.com/microsoft/generative-ai-for-beginners

#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

#python #chatbot #chatbots #chatgpt #chatgpt_4 #chatgpt_api #chatgpt_free #chatgpt4 #free_gpt #gpt #gpt_3 #gpt_4 #gpt3 #gpt4 #gpt4_api #language_model #openai #openai_api #openai_chatgpt #python #reverse_engineering

The `gpt4free` project is a tool that allows you to use various AI models like GPT-3.5 and DALL-E 3 without paying for expensive APIs. Here’s how it helps you It supports multiple AI providers, including OpenAI, Bing, and others, allowing you to choose the best option for your needs.
- **Easy Installation** It includes a web UI that you can access locally, making it easy to interact with the AI models.
- **Customization** The project is open-source and actively maintained by a community of contributors, ensuring continuous improvements and new features.

Overall, `gpt4free` provides a flexible and cost-effective way to leverage advanced AI capabilities.

https://github.com/xtekky/gpt4free