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Tensorant is a platform for preparing datasets, fine-tuning open-weight AI models, evaluating results, and deploying models for application use. Create training examples from documents, spreadsheets, or Hugging Face datasets, review examples alongside their sources, and save versioned datasets for training and testing. Fine-tune supported models using LoRA or QLoRA through a workspace without managing training scripts or GPU configuration. Compare base and fine-tuned model performance on the same test examples, then publish a model through an OpenAI-compatible API for integration with applications using the OpenAI SDK or HTTP. Tensorant supports model deployments on your connected cloud GPU account, with run limits and automatic GPU shutdown when work ends. Data and adapters are stored on your own storage volume, and trained adapters can be downloaded as standard LoRA files or published to Hugging Face.
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