Results for “vlm”
45 skills
nvidia Tao Analyze Gaps Vlm Bcq
Extract false-positive and false-negative gaps from VLM binary-classification-question predictions by comparing model responses against ground truth, producing a structured JSONL file and summary report for downstream root-cause analysis.
2.2k · bundle
nvidia Vss Summarize Video
Summarize recorded video clips using the LVS microservice with a VLM fallback, producing a narrative summary with timestamped events.
2.2k · bundle
nvidia Jetson LLM Serve
Serve LLMs and VLMs on NVIDIA Jetson devices using vLLM or SGLang with optimized Docker containers and quantization presets.
2.2k · bundle
nvidia Vss Deploy Dense Captioning
Deploy a standalone RT-VLM dense-captioning microservice and exercise its REST API endpoints for file upload, caption generation, streaming, chat completions, and Kafka integration.
2.2k · bundle
nvidia Tao Generate Image Grounding
Generates phrase-grounded bounding box annotations from image-caption pairs using a VLM, producing cleaned captions, referring expressions, and pixel-space bounding boxes.
2.2k · bundle
nvidia Nemo Mbridge Perf Moe Vlm Training
Provides practical guidance for training Mixture-of-Experts Vision-Language Models in Megatron Bridge, comparing FSDP and 3D-parallel approaches with lessons from recent multimodal experiments.
2.2k · bundle
More results
nvidia Jetson Inference Mem Tune
Recommends an inference runtime and memory-related launch flags for LLM/VLM workloads on NVIDIA Jetson devices, based on a live memory audit snapshot.
2.2k · bundle
nvidia Vss Generate Video Report
Generates video analysis reports by routing to a VLM backend for per-clip analysis or an analytics backend for incident-range reports, with deployment profile verification and URL rewriting.
2.2k · bundle
nvidia Nemo Mbridge Perf Sequence Packing
Validate and configure packed sequences and long-context training in Megatron-Bridge, distinguishing offline packed SFT for LLMs from in-batch packing for VLMs with correct context parallelism constraints.
2.2k · bundle
nvidia Jetson LLM Benchmark
Benchmark Jetson LLM/VLM serving performance across vLLM, llama.cpp, and Ollama with structured JSON output.
2.2k · bundle
ichichuang Serving Llms Vllm
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
0 · bundle
aniruddhaadak80 Serving Llms Vllm
vLLM: high-throughput LLM serving, OpenAI API, quantization.
0 · bundle
orchestra-research Serving Llms Vllm
Deploy and serve LLMs with high throughput using vLLM's PagedAttention and continuous batching. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism for production inference.
10.4k · bundle
orchestra-research Tensorrt LLM
Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency on NVIDIA GPUs (A100/H100).
10.4k · bundle
tianhao909 Serving Llms Vllm
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
1 · bundle
qcmuu Serving Llms Vllm
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
0 · bundle
jiachen-t-wang Docvqa A Dataset For Vqa On Document Images Arxiv 2007 00398
DocVQA: A Dataset for VQA on Document Images
6
q2805187159 Serving Llms Vllm
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
3 · bundle
jiachen-t-wang Glamm Pixel Grounding Large Multimodal Model Arxiv 2311 0335
GLaMM: Pixel Grounding Large Multimodal Model
6
nvidia Nemo Automodel Recipe Development
Create and modify NeMo AutoModel training and evaluation recipes, including YAML structure, builders, and execution flow.
2.2k · bundle
nvidia Jetson Speculative Decoding
Reduce per-token latency on Jetson vLLM servers by appending speculative decoding configuration, with guidance on when to enable and how to benchmark the improvement.
2.2k · bundle
nvidia Vss Ask Video
Ask visual questions about video clips using a VSS agent's video_understanding tool, requiring a fresh look at frames rather than prior metadata or search results.
2.2k · bundle
qcmuu Tensorrt LLM
Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.
0 · bundle
oyi77 LLM Deployment
Deploy and serve LLMs in production with vLLM, Ollama, TGI, and llama.cpp, including quantization and GPU optimization.
10
jiachen-t-wang Snli Ve Visual Entailment Dataset Arxiv 1901 06706v1
SNLI-VE: Visual Entailment Dataset
6
ranbot-ai LLM Ops
LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.
6
levalencia LLM CLI
Process textual and multimedia files with various LLM providers using the llm CLI. Supports both non-interactive and interactive modes with model selection, config persistence, and file input handling.
3 · bundle
majiayu000 Ml
Guides machine learning development with experiment tracking, hyperparameter optimization, model registry, and MLOps pipeline integration.
567 · bundle
tianhao909 Tensorrt LLM
Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.
1 · bundle
orchestra-research Blip 2 Vision Language
Generate image captions, answer visual questions, and perform image-text retrieval using BLIP-2's Q-Former architecture with frozen vision encoders and LLMs.
10.4k · bundle
comeonoliver Mvp
Builds a Streamlit and FastAPI RAG application that lets users upload documents and query them with natural language through LM Studio.
61
sinhoneyy LLM Ops
LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.
11
kbarbel640-del Rlm
Executes Python code iteratively via an MCP bridge to produce verified results for calculations, data analysis, and task decomposition.
1 · bundle
doriangallo LLM Ops
LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.
1
jrennie99-glitch Turboquant
KV cache compression for LLM inference — 4.4x compression, 2x context capacity, near-lossless quality. ICLR 2026 paper implementation with vLLM integration.
0
jiachen-t-wang Mmbench Is Your Multi Modal Model An All Around Player Arxiv
MMBench: Is Your Multi-modal Model an All-around Player?
6