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🤯 𝗔 𝗻𝗲𝘄 𝟳𝟬𝗕 𝗼𝗽𝗲𝗻-𝘄𝗲𝗶𝗴𝗵𝘁𝘀 𝗟𝗟𝗠 𝗯𝗲𝗮𝘁𝘀 𝗖𝗹𝗮𝘂𝗱𝗲-𝟯.𝟱-𝗦𝗼𝗻𝗻𝗲𝘁 𝗮𝗻𝗱 𝗚𝗣𝗧-𝟰𝗼!
🤯 𝗔 𝗻𝗲𝘄 𝟳𝟬𝗕 𝗼𝗽𝗲𝗻-𝘄𝗲𝗶𝗴𝗵𝘁𝘀 𝗟𝗟𝗠 𝗯𝗲𝗮𝘁𝘀 𝗖𝗹𝗮𝘂𝗱𝗲-𝟯.𝟱-𝗦𝗼𝗻𝗻𝗲𝘁 𝗮𝗻𝗱 𝗚𝗣𝗧-𝟰𝗼!
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@mattshumer
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, CEO from Hyperwrite AI, had an idea he wanted to try out: why not fine-tune LLMs to always output their thoughts in specific parts, delineated by <thinking> tags?
, CEO from Hyperwrite AI, had an idea he wanted to try out: why not fine-tune LLMs to always output their thoughts in specific parts, delineated by <thinking> tags?
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Even better: inside of that, you could nest other sections, to reflect critically on previous output. Let’s name this part <reflection>. Planning is also put in a separate step.
Even better: inside of that, you could nest other sections, to reflect critically on previous output. Let’s name this part <reflection>. Planning is also put in a separate step.
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He named the method “Reflection tuning” and set out to fine-tune a Llama-3.1-70B with it.
He named the method “Reflection tuning” and set out to fine-tune a Llama-3.1-70B with it.
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Well it turns out, it works mind-boggingly well!
Well it turns out, it works mind-boggingly well!
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🤯 Reflection-70B beats GPT-4o, Sonnet-3.5, and even the much bigger Llama-3.1-405B!
🤯 Reflection-70B beats GPT-4o, Sonnet-3.5, and even the much bigger Llama-3.1-405B!
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𝗧𝗟;𝗗𝗥
𝗧𝗟;𝗗𝗥
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🥊 This new 70B open-weights model beats GPT-4o, Claude Sonnet, et al.
🥊 This new 70B open-weights model beats GPT-4o, Claude Sonnet, et al.
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⏰ 405B in training, coming soon
⏰ 405B in training, coming soon
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📚 Report coming next week
📚 Report coming next week
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⚙️ Uses GlaiveAI synthetic data
⚙️ Uses GlaiveAI synthetic data
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🤗 Available on HF!
🤗 Available on HF!
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I’m starting an Inference Endpoint right now for this model to give it a spin!
I’m starting an Inference Endpoint right now for this model to give it a spin!
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Check it out 👉 
Check it out 👉 
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https://huggingface.co/mattshumer/Reflection-Llama-3.1-70B
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mattshumer/Reflection-Llama-3.1-70B
https://huggingface.co/mattshumer/Reflection-Llama-3.1-70B
🤯 𝗔 𝗻𝗲𝘄 𝟳𝟬𝗕 𝗼𝗽𝗲𝗻-𝘄𝗲𝗶𝗴𝗵𝘁𝘀 𝗟𝗟𝗠 𝗯𝗲𝗮𝘁𝘀 𝗖𝗹𝗮𝘂𝗱𝗲-𝟯.𝟱-𝗦𝗼𝗻𝗻𝗲𝘁 𝗮𝗻𝗱 𝗚𝗣𝗧-𝟰𝗼!

@mattshumer, CEO from Hyperwrite AI, had an idea he wanted to try out: why not fine-tune LLMs to always output their thoughts in specific parts, delineated by <thinking> tags?

Even better: inside of that, you could nest other sections, to reflect critically on previous output. Let’s name this part <reflection>. Planning is also put in a separate step.

He named the method “Reflection tuning” and set out to fine-tune a Llama-3.1-70B with it.

Well it turns out, it works mind-boggingly well!

🤯 Reflection-70B beats GPT-4o, Sonnet-3.5, and even the much bigger Llama-3.1-405B!

𝗧𝗟;𝗗𝗥
🥊 This new 70B open-weights model beats GPT-4o, Claude Sonnet, et al.
⏰ 405B in training, coming soon
📚 Report coming next week
⚙️ Uses GlaiveAI synthetic data
🤗 Available on HF!

I’m starting an Inference Endpoint right now for this model to give it a spin!

Check it out 👉 https://huggingface.co/mattshumer/Reflection-Llama-3.1-70B
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