Search results
Results From The WOW.Com Content Network
The GGUF (GGML Universal File) [26] file format is a binary format that stores both tensors and metadata in a single file, and is designed for fast saving, and loading of model data. [27] It was introduced in August 2023 by the llama.cpp project to better maintain backwards compatibility as support was added for other model architectures.
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.
Like earlier seq2seq models, the original transformer model used an encoder-decoder architecture. The encoder consists of encoding layers that process all the input tokens together one layer after another, while the decoder consists of decoding layers that iteratively process the encoder's output and the decoder's output tokens so far.
The model architecture remains largely unchanged from that of LLaMA-1 models, but 40% more data was used to train the foundational models. [26] The accompanying preprint [26] also mentions a model with 34B parameters that might be released in the future upon satisfying safety targets. LLaMa 2 includes foundation models and models fine-tuned for ...
Mamba [a] is a deep learning architecture focused on sequence modeling. It was developed by researchers from Carnegie Mellon University and Princeton University to address some limitations of transformer models, especially in processing long sequences. It is based on the Structured State Space sequence (S4) model. [2] [3] [4]
Mathstral 7B is a model with 7 billion parameters released by Mistral AI on July 16, 2024, focusing on STEM subjects. [25] The model was produced in collaboration with Project Numina, [23] and was released under the Apache 2.0 License with a context length of 32k tokens. [25] [21] Codestral 22B May 2024: 22 Mistral Non-Production License
LangChain was launched in October 2022 as an open source project by Harrison Chase, while working at machine learning startup Robust Intelligence. The project quickly garnered popularity, [3] with improvements from hundreds of contributors on GitHub, trending discussions on Twitter, lively activity on the project's Discord server, many YouTube tutorials, and meetups in San Francisco and London.
Since its inception, researchers in the field have raised philosophical and ethical arguments about the nature of the human mind and the consequences of creating artificial beings with human-like intelligence; these issues have previously been explored by myth, fiction and philosophy since antiquity. [23]