Explore

15 technologies shown

• LangChain framework Framework for composing language models with retrieval, tools and memory.
• LlamaIndex framework Data framework focused on ingesting, indexing and querying private knowledge.
• PyTorch framework The dominant deep learning framework, built around dynamic computation graphs.
• TensorFlow framework Google's deep learning framework, oriented toward deployment at scale.
• Sentence Transformers framework Library for embedding sentences and passages into vectors.
• Keras framework High-level modelling API that runs on several backends.
• Ray framework Distributed execution framework for scaling Python workloads.
• DSPy framework Builds model pipelines as programs whose prompts are optimised rather than written.
• DeepSpeed framework Training optimisation library for large models across many GPUs.
• AutoGen framework Framework for multi-agent conversations where agents critique each other.
• JAX framework NumPy-like array library with automatic differentiation and XLA compilation.
• Unsloth framework Fine-tuning implementation with hand-written kernels for speed and low memory.
• CrewAI framework Defines agent teams with roles and tasks, and runs them in order.
• Haystack framework Framework for building retrieval and question-answering pipelines.
• Axolotl framework Configuration-driven fine-tuning runner for many model architectures.