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togethercomputer
GitHub-Creator-Profil

togethercomputer

Repository-Ansicht von 28 gesammelten Skills in 4 GitHub-Repositories.

gesammelte Skills
28
Repositories
4
aktualisiert
17. Aug. 2026
Repository-Explorer

Repositories und repräsentative Skills

together-gpu-clusters
Netzwerk- und Computersystemadministratoren

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…

17. Aug. 2026
together-audio
Softwareentwickler

Text-to-speech and speech-to-text via Together AI, including REST, streaming, and realtime WebSocket TTS, plus transcription, translation, diarization, timestamps, and live STT. Reach for it whenever the user needs audio in or audio out on Together AI rather…

7. Aug. 2026
together-chat-completions
Softwareentwickler

Real-time and streaming text generation via Together AI's OpenAI-compatible chat/completions API, including multi-turn conversations, tool and function calling, structured JSON outputs, and reasoning models. Reach for it whenever the user wants to build or…

23. Juli 2026
together-evaluations
Softwareentwickler

LLM-as-a-judge evaluation framework on Together AI. Classify, score, and compare model outputs, select judge models, use external-provider judges or targets, poll results and download reports. Reach for it whenever the user wants to benchmark outputs, grade…

23. Juli 2026
together-dedicated-containers
Softwareentwickler

Custom Dockerized inference workers on Together AI's managed GPU infrastructure. Build with Sprocket SDK, configure with Jig CLI, submit async queue jobs, and poll results. Reach for it whenever the user needs container-level control rather than a standard…

23. Juli 2026
together-dedicated-model-inference
Softwareentwickler

Deploy and operate models on dedicated GPUs with Together AI's Dedicated Model Inference (DMI, the v2 dedicated endpoints API): beta endpoints, deployments, deployment profiles and hardware configs, autoscaling, traffic splitting, A/B tests, shadow…

23. Juli 2026
together-embeddings
Softwareentwickler

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…

23. Juli 2026
together-fine-tuning
Softwareentwickler

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…

23. Juli 2026
Es werden 8 von 14 gesammelten Skills angezeigt.
add-jit-kernel
nicht klassifiziert

Step-by-step tutorial for adding a new lightweight JIT CUDA kernel to sglang's jit_kernel module

9. Aug. 2026
cookbook-add-model
nicht klassifiziert

Add a new model to the SGLang Cookbook (docs/, Mintlify), config-driven format — instantiate the model-agnostic template into a per-model config (+ benchmarks) JSX under src/snippets/configs/, an MDX page, the docs.json nav entry, NEW-tag hygiene, and the…

9. Aug. 2026
llm-torch-profiler-analysis
nicht klassifiziert

Unified LLM torch-profiler triage skill for `sglang`, `vllm`, `TensorRT-LLM`, and `TokenSpeed`. Use it to inspect an existing `trace.json(.gz)` or profile directory, or to drive live profiling against a running server when supported and return one three-table…

9. Aug. 2026
sglang-runtime-context
nicht klassifiziert

How SGLang's runtime configuration and process-global state are organized (RuntimeContext tiers, publish + namespace config bags, the pristine ServerArgs seed, override entry points, resource/stream/buffer leases, per-forward flags), the CI guardrails that…

9. Aug. 2026
sglang-diffusion-add-model
nicht klassifiziert

Use when adding a new diffusion model or Diffusers pipeline to SGLang.

9. Aug. 2026
sglang-diffusion-benchmark-profile
nicht klassifiziert

Use when benchmarking denoise latency or profiling a diffusion bottleneck in SGLang.

9. Aug. 2026
sglang-diffusion-modelopt-quant
nicht klassifiziert

Use when quantizing a diffusion DiT with NVIDIA ModelOpt and making the resulting FP8 or NVFP4 checkpoint loadable, verifiable, and benchmarkable in SGLang Diffusion.

9. Aug. 2026
sglang-diffusion-performance
nicht klassifiziert

Use when choosing the fastest SGLang Diffusion flags for a model, GPU, and VRAM budget.

9. Aug. 2026
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