How to Fine-Tune and Train LLMs With Your Own Data EASILY and FAST With AutoTrain

Welcome to our channel, where we delve into the cutting-edge realm of machine learning innovation! In this video, we're thrilled to introduce you to AutoTrain, an incredible solution that's set to transform the way you approach training and fine-tuning machine learning models. 🚀

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Video Highlights:
🎯 Simplified Approach: AutoTrain promises to simplify the intricate process of model development by offering a user-friendly interface that requires no coding expertise.
📈 Effortless Workflow: Learn how users can easily upload their datasets, choose a model, specify GPU preferences, and fine-tune hyperparameters for seamless model training.
🌐 Accessibility Matters: Discover how AutoTrain caters to a wide range of users, with accessibility through both Hugging Face platform and Google Colab.
⏱️ Rapid Model Deployment: Explore the appeal of deploying state-of-the-art models within minutes, catering to quick results for projects.
🛠️ Flexibility in Model Selection: Find out how AutoTrain's adaptability allows users to tailor models to specific tasks and datasets.
💲 Transparent Pricing: Get insights into the pivotal role of pricing in determining the app's utility and accessibility.
📊 User-Friendly Evolution: Join us in discussing how AutoTrain aims to democratize machine learning model development.

Key Takeaways:
AutoTrain streamlines the model development cycle, making it accessible to both novices and experts. Its promise of rapid deployment, coupled with its adaptability and ease of use, positions it as an invaluable asset for research, prototyping, and production environments.

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Additional Tags:
Machine Learning, Model Development, AutoTrain, Training Models, Fine-Tuning, User-Friendly Interface, Rapid Deployment, Hyperparameter Tuning, Hugging Face, Google Colab, Accessibility, Innovation, Democratizing ML, Technical Expertise, Transparent Pricing.

Hashtags:
#MachineLearning #AutoTrain #ModelDevelopment #UserFriendlyML #Innovation #MLDemocratization #RapidModelDeployment #HyperparameterTuning

Thanks for tuning in, and let's dive into the exciting world of AutoTrain! 🌟

[Because_Reasons]

Would have been nice to have another video showcasing how to create the training data-set.

[stephenthumb]

for LLM's the current NOT advanced Autotrain is not there yet. the data and the type of model it wants to train is not the typical alpaca format QA instruction type LLM most people expect. Not sure why huggingface built it that way. if you want to train with huggingface then you'll need to use the advanced autotrain which again unfortunately doesn't really work well in the huggingface space. it works fine in colab or your own server but the huggingface space crashes all the time. some words for those starting out...

[vaishakhskamath]

can we use use to train text prediction .... i have lots of sentences of other language

[ikamanu]

Heard about this. Looking forward to checking it out. Thanks for sharing.

[PankajSingh-zywy]

how to make my own data set? I want to train it with my java code base so that it can type code for me.

[Suchtzocker]

why dont people train into one dataset and update it together ? why is everyone training his own little thing instead of making a 400gb file wich i would download tbh ...

[mastamindchaan]

I think I'm too stupid for that.
I want to fine tune the model with my data.
“AutoTrain” wants me to upload a .csv or .jsonl.
Can I write 1.000 words in one “instruction” in a .csv and have a text with 10.000 words in one output?

I want the model to be trained on my data.
If I write short sentences as a question/answer in a .csv, it doesn't make any sense.
Instruction: "Is water wet" Output "yes water is wet".
Chatgpt can do that anyway, it only helps with text adventures or something similar.

[AlgorithmicEchoes]

Is it possible to connect the finetuned model to Quoras Poe? Poe provides a way to developers to connect self managed servers. Can you please suggest?

[MicaleAntonio]

Does auto train do multi-label classification?

[harshitdtu]

is there any free alternative for auto training

[sharadkant]

How can auto train using "mosaicml/mpt-7b-chat" model
Below code is giving error
!autotrain llm\
--train\
--project_name resume_100_MPT_llm\
--model mosaicml/mpt-7b-chat\
--data_path
--use_peft\
--use_int4\
--learning_rate 2e-4 \
--train_batch_size 2 \
--num_train_epochs 3\
--trainer sft\
--model_max_length 2048\
--block_size 2048\