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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
🦖 X—LLM: Cutting Edge & Easy LLM Finetuning
| Date | Stars |
|---|---|
| 2026-07-31 | 410 |
| 2026-08-05 | 410 |
| 2026-09-03 | 410 |
| 2026-09-15 | 410 |
| 2026-09-20 | 410 |
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# 🦖 X—LLM: Cutting Edge & Easy LLM Finetuning <div align="center"> [](https://github.com/BobaZooba/xllm/actions/workflows/build.yaml) [](https://github.com/BobaZooba/xllm/blob/main/LICENSE) [](https://github.com/BobaZooba/xllm/releases) [](https://pypi.org/project/xllm/) [](https://pypi.org/project/xllm/) [](https://pypi.org/project/xllm/) [](https://github.com/modelfront/predictor/blob/master/.pre-commit-config.yaml) [](https://github.com/psf/black) [](https://github.com/astral-sh/ruff) [](http://mypy-lang.org/) [](https://codecov.io/gh/BobaZooba/xllm) [](https://discord.gg/5znbxBgwZP) Cutting Edge & Easy LLM Finetuning using the most advanced methods (QLoRA, DeepSpeed, GPTQ, Flash Attention 2, FSDP, etc) Developed by [Boris Zubarev](https://t.me/BobaZooba) | [CV](https://docs.google.com/document/d/1BhFvIHQ1mpm81P-n2A-lhNac-U2wOGc6F2uS9gKvk88/edit?usp=sharing) | [LinkedIn](https://www.linkedin.com/in/boriszubarev/) | [[email protected]](mailto:[email protected]) </div> # Why you should use X—LLM 🪄 Are you using **Large Language Models (LLMs)** for your work and want to train them more efficiently with advanced methods? Wish to focus on the data and improvements rather than repetitive and time-consuming coding for LLM training? **X—LLM** is your solution. It's a user-friendly library that streamlines training optimization, so you can **focus on enhancing your models and data**. Equipped with **cutting-edge training techniques**, X—LLM is engineered for efficiency by engineers who understand your needs. **X—LLM** is ideal whether you're **gearing up for production** or need a **fast prototyping tool**. ## Features - Hassle-free training for Large Language Models - Seamless integration of new data and data processing - Effortless expansion of the library - Speed up your training, while simultaneously reducing model sizes - Each checkpoint is saved to the 🤗 HuggingFace Hub - Easy-to-use integration with your existing project - Customize almost any part of your training with ease - Track your training progress using `W&B` - Supported many 🤗 Transformers models like `Yi-34B`, `Mistal AI`, `Llama 2`, `Zephyr`, `OpenChat`, `Falcon`, `Phi`, `Qwen`, `MPT` and many more - Benefit from cutting-edge advancements in LLM training optimization - QLoRA and fusing - Flash Attention 2 - Gradient checkpointing - bitsandbytes - GPTQ (including post-training quantization) - DeepSpeed - FSDP - And many more # Quickstart 🦖 ### Installation `X—LLM` is tested on Python 3.8+, PyTorch 2.0.1+ and CUDA 11.8. ```sh pip install xllm ``` Version which include `deepspeed`, `flash-attn` and `auto-gptq`:
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:43637baf91255309, topic:large-language-models, topic:llm, topic:gpt