Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
- fine-tuning
- llama
- llm
- peft
Repository Index
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Faster Whisper transcription with CTranslate2
- deep-learning
- inference
- quantization
- speech-recognition
TranslatedChinese LLaMA & Alpaca LLMs + local CPU/GPU training and deployment
- llm
- plm
- pre-trained-language-models
- alpaca
Translated[🔥updating ...] AI automated quantitative trading robot (fully local deployment) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
- funds
- machine-learning
- pytrade
- quantitative-finance
A vector index built on TurboQuant, written in Rust with Python bindings
- ann
- avx512
- embeddings
- faiss
A 2.78-trillion-parameter Kimi K3 running inference on a single CPU in 8.24 GB of RAM. Portable C99: no BLAS, no framework, no GPU.
- avx2
- c99
- cpu-inference
- deep-learning
QLoRA: Efficient Finetuning of Quantized LLMs
Accessible large language models via k-bit quantization for PyTorch.
- llm
- machine-learning
- pytorch
- qlora
2bit quants, kernels and runtime for consumer devices.
Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.
Run GLM-5.3 (744B), GLM-5.3-Flash (321B), DeepSeek-V4.1-Flash (748B) and MiniMax-M3.1-Flash (428B) on your own GPUs - one engine, one dashboard, OpenAI- and Anthropic-compatible API.
Serve large Qwen models fast on the GPUs you actually own. Qwen3.8-27B on a single 24 GB card with vLLM: 127 tok/s single-user (381 when the answer quotes the prompt), ~1,035 tok/s at 64 concurrent, 150k-262k context. vLLM patches, requant pipeline, benchmarks.
- kv-cache
- llm-inference
- local-llm
- quantization
A very fast and versatile markdown toolchain. Output to AST, React, React Native, SolidJS, Vue, HTML, and more!
Cross-vendor 3D Gaussian Splatting trainer - video to splat to mesh, Vulkan or CUDA.
- 3d-gaussian-splatting
- gaussian-splatting
- 3d-reconstruction
- 3dgs
Dataflow compiler for QNN inference on FPGAs
🐋 Run 284B DeepSeek-V4-Flash (<59GiB RAM, 44.4 tok/s pp, 9.1-14.7 tok/s) & 30B MoEs (25-111 tok/s) on a pure 64GB CPU at 256K ctx (0 GPUs). SwiGLU-H2, Stockfish-PVS L3 & 13ms Claude Code restore.
37 tok/s from Qwen3-Next-80B (48 GB) on a 32 GB laptop, 24 without drafts vs 2.8 for llama.cpp; reading 62 vs 16 tok/s. Faster than llama.cpp on all 13 models compared in Q4_K_M. LLMs bigger than your RAM, pure C, CPU or GPU.
- avx2
- c
- cpu-inference
- gguf
QKeras: a quantization deep learning library for Tensorflow Keras
- deep-learning
- quantization
- quantized-neural-networks
- hardware-acceleration
Smaller images, same picture. Compress PNGs to PNG or WebP with automatic quality. PNG output is 8–12% smaller than TinyPNG at equal quality on the median image. Command line and browser.
Xolotl: run DeepSeek-V4.1-Flash, all 552B, as a local coding agent on one gaming PC (RTX 4090 + 110 GB RAM): ~33 tok/s on agent tasks, ~41 in fast mode, 512K context. Plus GLM-5.3-Flash, Qwen3.8 and LFM3-Omni. MoE experts tiered across VRAM, pinned RAM and NVMe, with Xolotl Direct NVMe->VRAM. OpenAI + Anthropic API.
Fast, exact inference for StartLux-Decision models on NVIDIA GPUs: the released GGUF files on int8 and 4-bit tensor cores, behind the /v1/systemone API, with up to 5.3× lower latency than vLLM in FP8 and bit-identical answers.
- calibration
- cuda
- cuda-graphs
- decision-making
Official library for RaBitQ vector quantization and approximate nearest-neighbor search, in C++ and Python.
- nearest-neighbor-search
- quantization
- vector-database
- vector-search
Translated🐋 Complete guide in Russian: how to install and run DeepSeek locally (V4, R1) on PC, Mac and server — Ollama, llama.cpp, LM Studio, vLLM, Open WebUI, API, RAG, agents, fine-tuning, best tips and tricks
- ai-agents
- deepseek
- deepseek-r1
- deepseek-v4
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
- tensorflow-2
- tensorflow-lite
- on-device-ml
- model-quantization