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Found 6 Skills
LoRA, full fine-tuning, DPO preference tuning, VLM training, function-calling tuning, reasoning tuning, and BYOM uploads on Together AI. Reach for it whenever the user wants to adapt a model on custom data rather than only run inference, evaluate outputs, or host an existing model.
On-demand and reserved GPU clusters (H100, H200, B200) on Together AI with Kubernetes or Slurm orchestration, shared storage, credential management, and cluster scaling for ML and HPC jobs. Reach for it when the user needs multi-node compute or infrastructure control rather than a managed model endpoint.
Dense vector embeddings, semantic search, RAG pipelines, and reranking via Together AI. Generate embeddings with open-source models and rerank results behind dedicated endpoints. Reach for it whenever the user needs vector representations or retrieval quality improvements rather than direct text generation.
Text-to-speech (TTS) and speech-to-text (STT) via Together AI. TTS models include Orpheus, Kokoro, Cartesia Sonic, Rime, MiniMax with REST, streaming, and WebSocket support. STT models include Whisper and Voxtral. Use when users need voice synthesis, audio generation, speech recognition, transcription, TTS, STT, or real-time voice applications.
Generate videos from text and image prompts via Together AI. 15+ models including Veo 2/3, Sora 2, Kling 2.1, Hailuo 02, Seedance, PixVerse, Vidu. Supports text-to-video, image-to-video, keyframe control, and reference images. Use when users want to generate videos, create video content, animate images, or work with any video generation task.
Generate text embeddings and rerank documents via Together AI. Embedding models include BGE, GTE, E5, UAE families. Reranking via MixedBread reranker. Use when users need text embeddings, vector search, semantic similarity, document reranking, RAG pipeline components, or retrieval-augmented generation.