yandex/YaLM-100B
YaLM 100B
YaLM-100B is a large language model and open-weights AI model designed for generating and processing natural language text. It functions as a multilingual text generator optimized for producing and understanding human language content specifically in English and Russian.
The model is built for large scale language modeling and open source AI research, providing a foundation for text-based machine learning tasks. It utilizes a decoder-only transformer architecture with a multilingual embedding space to map English and Russian text into a shared vector space.
Its broader capabilities cover natural language processing, including the ability to generate written content and process multiple languages through predictive token sampling.
Features
- Prompt-Based Text Generation - Generates written content conditioned on input prompts using a large-scale generative model.
- Decoder Architectures - Utilizes a decoder-only transformer architecture to predict the next token in a sequence autoregressively.
- Multilingual Text Generation - Generates human-like text in both English and Russian using a single optimized model.
- Large Language Models - Provides a large-scale language model designed for diverse natural language processing tasks.
- Multilingual Text Embeddings - Maps English and Russian text into a shared multilingual embedding space to maintain semantic meaning.
- Natural Language Processing - Processes and understands natural language content across multiple linguistic regions, specifically English and Russian.
- Distribution-Based Sampling - Employs probability distribution-based sampling and greedy selection to determine the final output tokens.
- Model Scaling - Increases reasoning ability and capacity by stacking a high number of identical transformer blocks.
- Open-Weights Models - Provides pre-trained model weights openly to developers and researchers for machine learning tasks.
- Causal Masking - Uses a causal self-attention mechanism to restrict the model from looking at future tokens during training.
- Language Model Research - Serves as a foundation model for researchers to study and improve large-scale language model behavior.
- Decoder Models - Large-scale autoregressive language model.
- General Purpose Models - Large-scale autoregressive model for diverse generative language tasks.
- Large Language Models - Large-scale model for text generation and processing.
