content.raw: 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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content.value: 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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content.raw: It is created for consumer-size GPUs (24GB) covering the full end-to-end lifecycle with: 
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content.value: It is created for consumer-size GPUs (24GB) covering the full end-to-end lifecycle with: 
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content.raw: 💡Define and understand use cases for fine-tuning
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content.value: 💡Define and understand use cases for fine-tuning
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content.raw: 🧑🏻‍💻 Setup of the development environment
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content.value: 🧑🏻‍💻 Setup of the development environment
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content.raw: 🧮 Create and prepare dataset (OpenAI format)
content.type: text
content.value: 🧮 Create and prepare dataset (OpenAI format)
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content.raw: 🏋️‍♀️ Fine-tune LLM using TRL and the SFTTrainer
content.type: text
content.value: 🏋️‍♀️ Fine-tune LLM using TRL and the SFTTrainer
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content.raw: 🥇 Test and evaluate the LLM
content.type: text
content.value: 🥇 Test and evaluate the LLM
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content.raw: 🚀 Deploy for production with TGI
content.type: text
content.value: 🚀 Deploy for production with TGI
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content.raw: 👉  
content.type: text
content.value: 👉  
content.href: https://www.philschmid.de/fine-tune-llms-in-2024-with-trl
content.raw: https://www.philschmid.de/fine-tune-llms-in-2024-with-trl
content.type: link
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content.raw: Coming soon: Advanced Guides for multi-GPU/multi-Node full fine-tuning and alignment using DPO & KTO. 🔜
content.type: text
content.value: Coming soon: Advanced Guides for multi-GPU/multi-Node full fine-tuning and alignment using DPO & KTO. 🔜
rawContent: 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. 🔜
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reactions.reaction: 🤗
reactions.users: littletensor
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