Langtrain
Postman for fine-tuning LLMs
Langtrain launched on January 5, 2026 with 8 votes, #1,339 of 14,584 launches that month and more than 90% of that year's launches.
What it does
Train AI models locally, use offline forever. Langtrain Studio fine-tunes Llama, Mistral, Gemma on your GPU, no cloud uploads, no per-token fees. Download once, train offline. Real-time dashboard, LoRA/QLoRA support, one-click export. Your data stays on your machine. Own your AI infrastructure
The complete LLM training platform. Fine-tune 100+ open-source models with AdaptiveRank (beats Unsloth on cost), align with RLHF / PPO / GRPO / Constitutional AI, add AI Guardrails, deploy endpoints, run Agents, and monitor with LangVision — all in one place.
Fine-tune, align, and deploy open-source models on your own infrastructure. Built for enterprise teams that demand total data sovereignty. Annual subscriptions are refundable within 30 days of purchase. After 30 days, you can cancel and keep access until your billing cycle ends. Contact [email protected] for refunds. I don't have access to your company's specific refund policy. Please check your account settings, terms of service, or contact customer support for accurate information. Chat with your fine-tuned model the moment training ends. Compare outputs side-by-side against the base model with source citations. Annual subscriptions are refundable within 30 days of purchase. After 30 days,…from langtrain.xyz
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FineTuner2025 · nowhiteboards.io · ▲164NEW88 là nền tảng giải trí trực tuyến uy tín hàng đầu Châu Á với đa dạng sản phẩm, ưu đãi khủng và trải nghiệm an toàn bảo mật trên mọi thiết bị.
Tune LLaMa3.1 on Google Cloud TPUs2024 · github.com · ▲189Hey HN, we wanted to share our repo where we fine-tuned Llama 3.1 on Google TPUs. We’re building AI infra to fine-tune and serve LLMs on non-NVIDIA GPUs (TPUs, Trainium, AMD GPUs). The problem: Right now, 90% of LLM workloads run on NVIDIA GPUs, but there are equally powerful and more cost-effective alternatives out there. For example, training and serving Llama 3.1 on Google TPUs is about 30% cheaper than NVIDIA GPUs. But developer tooling for non-NVIDIA chipsets is lacking. We felt this pain ourselves. We initially tried using PyTorch XLA to train Llama 3.1 on TPUs, but it was rough: xla…
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