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What's the best way to fine-tune open LLMs in 2024? Look no further! 👀 I am excited to share “How to Fine-Tune LLMs in 2024 with Hugging Face” using the latest research techniques, including Flash Attention, Q-LoRA, OpenAI dataset formats (messages), ChatML, Packing, all built with Hugging Face TRL. 🚀
What's the best way to fine-tune open LLMs in 2024? Look no further! 👀 I am excited to share “How to Fine-Tune LLMs in 2024 with Hugging Face” using the latest research techniques, including Flash Attention, Q-LoRA, OpenAI dataset formats (messages), ChatML, Packing, all built with Hugging Face TRL. 🚀
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It is created for consumer-size GPUs (24GB) covering the full end-to-end lifecycle with: 
It is created for consumer-size GPUs (24GB) covering the full end-to-end lifecycle with: 
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💡Define and understand use cases for fine-tuning
💡Define and understand use cases for fine-tuning
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🧑🏻‍💻 Setup of the development environment
🧑🏻‍💻 Setup of the development environment
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🧮 Create and prepare dataset (OpenAI format)
🧮 Create and prepare dataset (OpenAI format)
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🏋️‍♀️ Fine-tune LLM using TRL and the SFTTrainer
🏋️‍♀️ Fine-tune LLM using TRL and the SFTTrainer
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🥇 Test and evaluate the LLM
🥇 Test and evaluate the LLM
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🚀 Deploy for production with TGI
🚀 Deploy for production with TGI
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👉  
👉  
link
https://www.philschmid.de/fine-tune-llms-in-2024-with-trl
https://www.philschmid.de/fine-tune-llms-in-2024-with-trl
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Coming soon: Advanced Guides for multi-GPU/multi-Node full fine-tuning and alignment using DPO & KTO. 🔜
Coming soon: Advanced Guides for multi-GPU/multi-Node full fine-tuning and alignment using DPO & KTO. 🔜
What's the best way to fine-tune open LLMs in 2024? Look no further! 👀 I am excited to share “How to Fine-Tune LLMs in 2024 with Hugging Face” using the latest research techniques, including Flash Attention, Q-LoRA, OpenAI dataset formats (messages), ChatML, Packing, all built with Hugging Face TRL. 🚀

It is created for consumer-size GPUs (24GB) covering the full end-to-end lifecycle with: 
💡Define and understand use cases for fine-tuning
🧑🏻‍💻 Setup of the development environment
🧮 Create and prepare dataset (OpenAI format)
🏋️‍♀️ Fine-tune LLM using TRL and the SFTTrainer
🥇 Test and evaluate the LLM
🚀 Deploy for production with TGI

👉  https://www.philschmid.de/fine-tune-llms-in-2024-with-trl

Coming soon: Advanced Guides for multi-GPU/multi-Node full fine-tuning and alignment using DPO & KTO. 🔜
❤️
andrewrreed Jofthomas victor stefan-jo s3nh osanseviero luqmanxyz philschmid kramp samusenps Csplk lunarflu julien-c hamedbabaeigiglou harpreetsahota dhuynh95 clem CultriX afrideva brekk andysalerno PriyankSisodia azimuth3d nuatmochoi mathiasn1 ashwinlimaye AdinaY vicgalle pardeep merve adamo1139 madroid mikr omaryshchenko alielfilali01 patchie2 celsowm Luciano santyzenith sbrandeis ramkrish120595 Utkarsh736
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🤗
littletensor
https://cdn-avatars.huggingface.co/v1/production/uploads/1648113222875-6141a88b3a0ec78603c9e784.png
Merve Noyan
merve
user
/avatars/245ec3b183919c079f8c5023b3f7ca9f.svg
CultriX
CultriX
user
/avatars/302fb28d27b64624c37c6755526f9d6f.svg
Zappa
zappa2005
user
https://cdn-avatars.huggingface.co/v1/production/uploads/6585a41eb378d311dcef0af5/UZrIVxAuf9GkUWUAcgeO1.jpeg
Mark kaave
MarcorpAI
user