Top Tweets for #LMFlow
#LMFlow now supports the fine-tuning of Qwen2 🤗🚀A SOTA
✅Full-parameter training
✅LoRA
✅QLoRA
🚧LISA: under integration
https://t.co/vxBRTKBUeM
After months of efforts, we are pleased to announce the evolution from Qwen1.5 to Qwen2. This time, we bring to you:
⭐ Base and Instruct models of 5 sizes, including Qwen2-0.5B, Qwen2-1.5B, Qwen2-7B, Qwen2-57B-A14B, and Qwen2-72B. Having been trained on data in 27 additional languages besides English and Chinese.
🌟 SOTA performance in a large number of benchmark evaluations. Significantly improved performance in coding and math.
🌠 Extended context length support up to 128K tokens with Qwen2-7B-Instruct and Qwen2-72B-Instruct.
📚 BLOG: https://t.co/qdN92SdUeQ
🤗 DEMO: https://t.co/LS3PxeWSw2
🤖 CODE: https://t.co/dfAfWytdUu

ChatML template is also supported in #LMFlow now 🚀
Just adding --conversation_template chatml and you are all set! 😉
- Example: https://t.co/ilyHIqUEGR
- Document: https://t.co/VauKpUZj1b
🦙 OrpoLlama-3-8B
Successful ORPO fine-tune of Llama 3 with ChatML template!
It was trained on 40K high-quality preference samples for 3 epochs. Sharing some details and benchmarks. 🧵
🤗 Model: https://t.co/c2sdaskFh6
🪟 Demo: https://t.co/w4z4EdRlsg

Phi-3 template supported in #LMFlow, waiting for the base model 👀
Try further tuning Phi-3-instruct in LMFlow with SFT/#LISA/#LoRA via 👇

phi-3 is here, and it's ... good :-).
I made a quick short demo to give you a feel of what phi-3-mini (3.8B) can do. Stay tuned for the open weights release and more announcements tomorrow morning!
(And ofc this wouldn't be complete without the usual table of benchmarks!)

@ClementDelangue Our training code and training data are fully open-source (https://t.co/oNIONeY5pe)! Feel free to use LMFlow to fine-tune your own models. #LMFlow #machinelearning
Hey everyone, happy weekend!😆 Our toolbox for finetuning large machine learning models LMFlow has some amazing updates that we wanna share with you!😉#AIGC #chatgptprompts #ArtificialIntelligence #LMFlow
You can download all the models here: [https://t.co/vQG0eIsa2H]
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