Post
Found out my ECCV paper is getting rejected because of a LaTeX compile error :(
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mattmdjaga
posted an update
25 minutes ago
Post
NEW HF 🤗 COURSE to help people dive into Computer Vision built by the HF community. Over the last 6 months the hugging face discord community has been hard at work developing a new computer vision course. Receive a Certificate of completion and share it on your socials 🤗.
https://huggingface.co/learn/computer-vision-course/unit0/welcome/welcome
https://huggingface.co/learn/computer-vision-course/unit0/welcome/welcome
Post
68
Finally!
My first post for the lovely community out there!
Here's a highly quantized finetuned version of gemma focused exclusively on Prompt Engineering. Write as ambiguous you want and leave the job to this model
zamal/gemma-7b-finetuned
My first post for the lovely community out there!
Here's a highly quantized finetuned version of gemma focused exclusively on Prompt Engineering. Write as ambiguous you want and leave the job to this model
zamal/gemma-7b-finetuned
Post
82
Okay, I can post now, Yayy!!
Sharing the OpenBioLLM-70B as the first post :)
Introducing OpenBioLLM-Llama3-70B & 8B: The most capable openly available Medical-domain LLMs to date! 🩺💊🧬
Outperforms industry giants like GPT-4, Gemini, Meditron-70B, Med-PaLM-1, and Med-PaLM-2 in the biomedical domain. 🏥📈 🌟
OpenBioLLM-70B delivers SOTA performance, setting a new state-of-the-art for models of its size. OpenBioLLM-8B model and even surpasses GPT-3.5, Gemini, and Meditron-70B! 🚀
Today's release is just the beginning! In the coming months, we'll be introducing:
- Expanded medical domain coverage 🧠
- Longer context windows 📜🔍
- Better benchmarks 📈🏆
- Multimodal capabilities🖥️🩺📊🔬
Medical-LLM Leaderboard: openlifescienceai/open_medical_llm_leaderboard
More detail : https://huggingface.co/blog/aaditya/openbiollm
Sharing the OpenBioLLM-70B as the first post :)
Introducing OpenBioLLM-Llama3-70B & 8B: The most capable openly available Medical-domain LLMs to date! 🩺💊🧬
Outperforms industry giants like GPT-4, Gemini, Meditron-70B, Med-PaLM-1, and Med-PaLM-2 in the biomedical domain. 🏥📈 🌟
OpenBioLLM-70B delivers SOTA performance, setting a new state-of-the-art for models of its size. OpenBioLLM-8B model and even surpasses GPT-3.5, Gemini, and Meditron-70B! 🚀
Today's release is just the beginning! In the coming months, we'll be introducing:
- Expanded medical domain coverage 🧠
- Longer context windows 📜🔍
- Better benchmarks 📈🏆
- Multimodal capabilities🖥️🩺📊🔬
Medical-LLM Leaderboard: openlifescienceai/open_medical_llm_leaderboard
More detail : https://huggingface.co/blog/aaditya/openbiollm
- 1 reply
phenixrhyder
posted an update
about 6 hours ago
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590
Midjourney Ai
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- 1 reply
nkasmanoff
posted an update
about 13 hours ago
Post
1063
I've put Llama 3 on a Raspberry Pi! And it can actually help me!
Would love to hear what you think :-) What should I do next so that it can flip a light switch for me?
Demo: https://youtu.be/OryGVbh5JZE
GitHub: https://github.com/nkasmanoff/pi-card
Would love to hear what you think :-) What should I do next so that it can flip a light switch for me?
Demo: https://youtu.be/OryGVbh5JZE
GitHub: https://github.com/nkasmanoff/pi-card
Post
940
DmitryRyumin
posted an update
about 16 hours ago
Post
905
🔥🚀🌟 New Research Alert - YOCO! 🌟🚀🔥
📄 Title: You Only Cache Once: Decoder-Decoder Architectures for Language Models 🔝
📝 Description: YOCO is a novel decoder-decoder architecture for LLMs that reduces memory requirements, speeds up prefilling, and maintains global attention. It consists of a self-decoder for encoding KV caches and a cross-decoder for reusing these caches via cross-attention.
👥 Authors: Yutao Sun et al.
📄 Paper: You Only Cache Once: Decoder-Decoder Architectures for Language Models (2405.05254)
📁 Repository: https://github.com/microsoft/unilm/tree/master/YOCO
📚 More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
🔍 Keywords: #YOCO #DecoderDecoder #LargeLanguageModels #EfficientArchitecture #GPUMemoryReduction #PrefillingSpeedup #GlobalAttention #DeepLearning #Innovation #AI
📄 Title: You Only Cache Once: Decoder-Decoder Architectures for Language Models 🔝
📝 Description: YOCO is a novel decoder-decoder architecture for LLMs that reduces memory requirements, speeds up prefilling, and maintains global attention. It consists of a self-decoder for encoding KV caches and a cross-decoder for reusing these caches via cross-attention.
👥 Authors: Yutao Sun et al.
📄 Paper: You Only Cache Once: Decoder-Decoder Architectures for Language Models (2405.05254)
📁 Repository: https://github.com/microsoft/unilm/tree/master/YOCO
📚 More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
🔍 Keywords: #YOCO #DecoderDecoder #LargeLanguageModels #EfficientArchitecture #GPUMemoryReduction #PrefillingSpeedup #GlobalAttention #DeepLearning #Innovation #AI
