LLM Fine-tuning

Algorithms and instructions for fine-tuning LLMs with FELT Labs

Full tutorial: https://medium.com/@breta.hajek/fine-tuning-large-language-models-with-felt-labs-full-guide-3f1c3fcc9af6

Does your project have a specific need for fine-tuning LLMs? Contact us at [email protected], and our team will help you with that!

Publishing Algorithm

Provider: https://provider.feltlabs.ai/
File URL: https://raw.githubusercontent.com/FELT-Labs/llm-finetuning/main/algorithm.py
Entry point: python3 $ALGO
Docker image: feltlabs/llm-compute:latest

Publishing Dataset

Access type: Compute Provider: https://provider.feltlabs.ai/
File URL: https://raw.githubusercontent.com/FELT-Labs/llm-finetuning/main/dataset.json

Run Fine-Tuning

Go to https://app.feltlabs.ai/learning/single and do following steps:

1. Select your dataset
2. Select fine-tuning algorithm
3. Pick hyperparameters
4. Start training

Inference

Use inference.ipynb notebook for running the inference. You can use it through Google Colab: https://colab.research.google.com/github/FELT-Labs/llm-finetuning/blob/main/inference.ipynb