Fine-tuning driven entirely by a YAML config.
Axolotl reduces a training run to one declarative file — model, dataset format, adapter, sequence length, distributed strategy — which makes experiments reproducible and diffable in a way that a folder of modified scripts never is. It handles multi-GPU via DeepSpeed and FSDP and supports sample packing for throughput.
Fine-tune a hundred different models from one interface.
Visual builder for agents and RAG flows, deployable as an API.
Fair-code workflow automation with AI steps built in.
Track the experiments, register the models, ship the good one.
A distributed vector database built for billion-scale collections.
A Rust vector engine with genuinely good payload filtering.
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