Generative AI engineering notebooks about Large Language Model customization
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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 engineering notebooks
This repository acts as an archive of the owners experience working with large language models neatly presented within jupyter 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
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.
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.
Personal GitHub repository for stashing resources on Large Language Models (LLM), including Jupyter Notebooks on open source LLMs, use-cases with Langchain and R&D paper review.
Implementation for the different ML tasks on Kaggle platform with GPUs.
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