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Spark Pulse is a web control plane for spark-vllm-docker

Inference and finnetunning of a VLM (LLama Vision 11b) using the Unsloth, PEFT libraries and torch.

Qwen3.6 vLLM Toolkit — Launcher + Templates, Optimized for 2×24 GB. vLLM launcher with an optimized hybrid chat template drawing from the best community fixes for Qwen 3.6 27B.

General Information, model certifications, and benchmarks for nm-vllm enterprise distributions

The official implementation of CVPR Workshop 2025 paper: Window Token Concatenation for Efficient Visual Large Language Models.

Professional CLI toolkit for Modal GPU workflows, Docker Compose deployments, Python runtimes, model serving, and account/billing management.

GPU orchestrator with vLLM sleep mode

Out-of-tree vLLM plugin and open format spec for NVFP4-CB / FP8-CB product-codebook weights — 2-6 bit-per-weight LLM quantization served on native Blackwell tensor cores.

Reward a Language Model with pancakes 🥞

Open-source framework for turning expert knowledge into PII-free synthetic conversational data and production-ready LoRA adapters.

Complete setup guide for a 2-node NVIDIA DGX Spark cluster — distributed training, CUDA inference with EXO, NCCL tuning for Grace Blackwell, NVMe-TCP shared storage, and 200 Gb/s direct fabric networking.

Taller: Modelos de lenguaje a tu medida. 2º Workshop Argentino de NLP, Córdoba 2023

Hotel-domain conversational assistant using Qwen2.5-7B-Instruct, focusing on practical, reproducible fine-tuning. It supports SFT + LoRA for a stable baseline, SFT + QLoRA for 7B model training with 4-bit quantization under limited GPU memory, and DPO to enhance responses via human preference pairs

Finetuning of Gemma-2 2B for structured output

[WACV 2026] The official implementation of the paper titled " End-to-End Fine-Tuning of 3D Texture Generation using Differentiable Rewards" accepted to IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2026

Finetuning Google's Gemma Model for Translating Natural Language into SQL

Advance information retrieval system that combines advanced indexing, machine learning, and personalized search to enhance academic research and document discovery.

The License Plate Recognition (LPR) System is a computer vision project designed to detect and recognize license plates in images or video streams.

Tracking exactly what happens to the internal "circuitry" (induction heads) of a 2-layer attention-only Transformer when forced to undergo domain adaptation from prose to structured Python code.

This repository contains a system for generating question-answer pairs for FINE-TUNING LLMs from the data you have.