In this quick and easy tutorial, we'll show you how to fine-tune powerful language models like Llama2 using AutoTrain,
AutoTrain is a no-code tool for model training and fine-tuning.
Whether you're a beginner or a pro, you'll learn step-by-step how to harness the full potential of LLMs with AutoTrain by finetuning them to specific tasks.
In order to utilize AutoTrain for fine-tuning we require 3 things:
1. Base model
2. Fine-tuning task
3. Preparing the dataset
Let us understand these step by step
Resources:
* AutoTrain: https://huggingface.co/autotrain
* Dataset formats:
[alpaca] https://huggingface.co/datasets/tatsu...
[guanaco] https://huggingface.co/datasets/timde...
Understanding Parameter Efficient Fine tuning (Peft): • Fine Tuning LLMs with limited GPU in ...
#generativeai #Autotrain #LLM #Tutorial #llama #gpt
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If you are a #btech student, #diploma in #computerscience, #graduate looking to #career #transition into #datascience , #machinelearning, #dataanalysis, this is a place for you
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Why learn from datahat??
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learners --- professionals by simplified data science
It provides a platform to learn, create and collaborate helping in the #career #transition to data science, machine learning and data analysis
Understand the broad domain of data science and its related subdomains in machine learning, data analysis, data engineering in a self paced, #structured and #guided learning
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Additionally, here are few more useful resources for beginners and curious data enthusiasts
1. kaggle: a platform to learn, practice, compete and win cash prizes [https://www.kaggle.com/]
2. paperswithcode: website presenting the latest in machine learning and data science research and the code implementations [https://paperswithcode.com/]
3. google colab: a platform to run code, build machine learning solutions, explore the capabilities of GPU and TPU without any hassle in setting up the environment: [https://colab.research.google.com/]
Remember, "the greatest investment ever made is investment in self growth and learning"
