Generative AI engineering notebooks about Large Language Model customization
-
Updated
Aug 16, 2023 - Jupyter Notebook
Generative AI engineering notebooks about Large Language Model customization
Notebooks for ML Tasks w/ Scikit and LLMs using Cohere, HuggingFace, LangChain, and OpenAI
Generative AI research updates, interview resources, notebooks and much more.
Generative AI engineering notebooks
This repository acts as an archive of the owners experience working with large language models neatly presented within jupyter notebooks
Libem notebooks.
Colab notebooks to understand LLMs
A comprehensive hub for updates on generative AI research, including interviews, notebooks, and additional resources.
Fine-Tune Your Own Llama 2 Model LOCALLY in a Colab Notebook
Collection of Jupyter Notebooks related to Generative AI.
Code refactoring using large language models in Jupyter notebooks
QA With Jupyter NoteBook(.ipynb) powered by LangChain & Anthropic
Run Dolly, the world’s first truly open instruction-tuned LLM, with your own prompts on IPUs
Sample code and notebooks for Generative AI on Google Cloud, including Gemini
A Python notebook showcasing various usecases of Langchain with LLMs such as OpenAI.
Notebook for Flan-T5 – an alternative to large language models like GPT-3 & GPT-4 for NLP tasks like named entity recognition and text generation.
Colab notebook for finetuning Microsoft's Phi-2-3B LLM for solving mathematical word problems using QLoRA
Pre-Training and Fine-Tuning transformer models using PyTorch and the Hugging Face Transformers library. Whether you're delving into pre-training with custom datasets or fine-tuning for specific classification tasks, these notebooks offer explanations and code for implementation.
A data analasys application in a Jupyter Notebook that is able to determine the efficiency of the GPT API and BERT in classifying scientific papers.
Add a description, image, and links to the large-language-models topic page so that developers can more easily learn about it.
To associate your repository with the large-language-models topic, visit your repo's landing page and select "manage topics."