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togethercomputer
Profil créateur GitHub

togethercomputer

Vue par dépôt de 28 skills collectés dans 4 dépôts GitHub.

skills collectés
28
dépôts
4
mis à jour
17 août 2026
explorateur de dépôts

Dépôts et skills représentatifs

together-gpu-clusters
Administrateurs de réseaux et de systèmes informatiques

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 août 2026
together-audio
Développeurs de logiciels

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 août 2026
together-chat-completions
Développeurs de logiciels

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 juil. 2026
together-evaluations
Développeurs de logiciels

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 juil. 2026
together-dedicated-containers
Développeurs de logiciels

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 juil. 2026
together-dedicated-model-inference
Développeurs de logiciels

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 juil. 2026
together-embeddings
Développeurs de logiciels

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 juil. 2026
together-fine-tuning
Développeurs de logiciels

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 juil. 2026
Affichage de 8 skills collectés sur 14.
add-jit-kernel
non classé

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

9 août 2026
cookbook-add-model
non classé

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 août 2026
llm-torch-profiler-analysis
non classé

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 août 2026
sglang-runtime-context
non classé

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 août 2026
sglang-diffusion-add-model
non classé

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

9 août 2026
sglang-diffusion-benchmark-profile
non classé

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

9 août 2026
sglang-diffusion-modelopt-quant
non classé

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 août 2026
sglang-diffusion-performance
non classé

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

9 août 2026
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