Mastering LLAMA-3 Fine Tuning 🦙 | Custom Data

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In this video, you'll learn:
How to install and set up Unslot for Lama 3 fine-tuning.
The optimal way to format your data for training.
Key training parameters and how to configure them for efficiency.
Performing inference with your fine-tuned Lama 3 model.
Saving and deploying your custom AI for various applications.
Unslot offers significant advantages, such as:

Up to 30x faster training compared to other methods.
Highly optimized memory usage, ideal for limited GPU resources.
Seamless integration with Hugging Face and other tools.
Easy conversion to various formats for diverse applications.
Whether you're a beginner or an experienced AI enthusiast, this video will equip you with the knowledge and skills to create your own personalized AI using Lama 3 and Unslot. Start building your custom AI assistant, chatbot, or text generator today!

Additional Resources:

Unslot GitHub Repository: [link to repo]
Hugging Face Lama 3 Model: [link to model]
AutoTrain Platform: [link to platform]
Don't forget to like, subscribe, and share this video with others who might find it helpful! Leave a comment below if you have any questions or suggestions.

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Fabulous video and very detailed! Keep up the fantastic work!

danielhanchen
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I have a .csv file. for train mistral-7b to language translation how convert to correct dataset format and load it .
csv file content example:
{ "en": "Did you find something?", "fr": "Par ici !" }
{ "en": "Here it is.", "fr": "Le voilà." }

KINGKING-lhgw
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