Elevate Your Models with Seamless Fine-Tuning
Accelerate custom model development using advanced workflows, secure enterprise infrastructure, and flexible scaling—whether on-prem or in your private cloud.
Jumpstart fine-tuning with optimized workflows and pre-defined configurations for LLMs, embedding/reranker models, and OCR. Extend the catalog with custom setups, letting you focus on innovation rather than infrastructure complexities.
Develop fully customized models using LoRa, QLoRa, ReLoRa, or GPTQ techniques. Optimize RAG performance with integrated fine-tuning for embedding or reranker models, supported by enterprise-grade reliability and flexible scaling options for diverse workloads.
Use the intuitive UI or CLI to monitor progress, compare experiments, and log key metrics. Manage fine-tuned models in a registry, and leverage built-in evaluation tools for language, embedding, and reranker models—plus integrated inference for custom deployments.
Expand datasets using synthetic data generation and negative sample mining. Quickly create Q&A pairs from private data or load custom formats. Leverage RLHF data from SecureLLM to further refine models, enhancing relevance and accuracy.
Merge & Quantize
Combine multiple models and perform on-the-fly quantization for efficient, lightweight deployments.
Integrated SkyPilot
Leverage SkyPilot to orchestrate on-prem compute and private cloud resources seamlessly for your fine-tuning jobs.
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Balance Cost & Performance
Benchmark accelerators, use spot instances with checkpointing, and optimize resources to meet both budget and performance goals.
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Accelerated Performance
Scale across multi-GPU, multi-node, FSDP, and DeepSpeed integrations, ensuring parallel processing for large-scale fine-tuning tasks.
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Auto Scale
Automatically scale up for demanding jobs, then reduce resources post-completion for maximum efficiency and cost savings.
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Enterprise-Grade Privacy
Use robust RBAC and CBAC integrations, ensuring only authorized teams handle sensitive data during the fine-tuning process.
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