Nixtla/mlforecast
Scalable machine 🤖 learning for time series forecasting.
Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning
Scalable machine 🤖 learning for time series forecasting.
A python library for user-friendly forecasting and anomaly detection on time series.
A Library for Advanced Deep Time Series Models for General Time Series Analysis.
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.6, DeepSeek-R1, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM4.5v, Gemma4, Llava, Phi4, ...) (AAAI 2025).
Time series forecasting with PyTorch
A unified library of SOTA model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
1 capture since 2026-06-02
pyproject.toml
· python · 27 dependencies
requirements.txt
· python · 11 dependencies
setup.cfg
· python · 0 dependencies
setup.py
· python · 0 dependencies
docs/requirements.txt
· python · 5 dependencies
.github/scripts/requirements.txt
· python · 2 dependencies