tailspin
| tailspin | gpt-llm-trainer | |
|---|---|---|
| 2 | 4 | |
| 5,072 | 3,811 | |
| - | - | |
| 9.6 | 5.4 | |
| 7 days ago | about 1 month ago | |
| Rust | Jupyter Notebook | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tailspin
gpt-llm-trainer
- FLaNK Stack Weekly 06 Nov 2023
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Show HN: Fine-tune your own Llama 2 to replace GPT-3.5/4
Very nice, thanks!
Check out what Matt Shumer put together as well: https://github.com/mshumer/gpt-llm-trainer.
I have used his trainer for auto distillation of GPT-4 into GPT3.5 fine tunes, but plan to do the same for Llama as well.
Cheers!
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[D] Anyone tried gpt-llm-trainer?
Hey guys, so I stumbled upon this Linkedin post, this guy was showing a jupyter notebook on google colab and was explaining step by step how to train your own model to accomplish very specific tasks, and I believe the base model he was using Llama 2 7B Fine tuning version. This is the github link: https://github.com/mshumer/gpt-llm-trainer
- GPT-LLM-Trainer
What are some alternatives?
lnav - Log file navigator
axolotl - Go ahead and axolotl questions
deepeval - The LLM Evaluation Framework
OpenPipe - Turn expensive prompts into cheap fine-tuned models
colored - (Rust) Coloring terminal so simple you already know how to do it !
Llama-2-Onnx
epick - Color picker for creating harmonic color palettes that works on Linux, Windows, macOS and web.
trieve - All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.
CML_AMP_Chroma-Server-For-Vector-DB - Host a Chroma Server for Vector DB and Semantic Search, accessible via REST API
open_model_zoo - Pre-trained Deep Learning models and demos (high quality and extremely fast)
openvino_notebooks - 📚 Jupyter notebook tutorials for OpenVINO™
vllm - A high-throughput and memory-efficient inference and serving engine for LLMs