RAPIDFlow: Recurrent Adaptable Pyramids with Iterative Decoding for Efficient Optical Flow Estimation
🖥 Github: https://github.com/hmorimitsu/ptlflow
📕 Paper: https://hmorimitsu.com/publication/2024-icra-rapidflow/
⚡️ Dataset: https://paperswithcode.com/dataset/kitti
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Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing
🖥 Github: https://github.com/wangkai930418/DPL
📕 Paper: https://arxiv.org/abs/2405.01496v1
🔥 Dataset: https://neurips.cc/virtual/2023/poster/72801
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Distillation for Multilingual Information Retrieval
🖥 Github: https://github.com/hltcoe/colbert-x
📕 Paper: https://arxiv.org/abs/2405.00977v1
🔥Docs: pypi.org/project/PLAID-X/
🔥Docs: pypi.org/project/PLAID-X/
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⚡️ Finetuning for Text Classification
If you're looking for something to do this weekend and want to do a little reading and coding, here's the latest chapter from the book Build an LLM from Scratch , on setting up a GPT model to classify SPAM messages with up to 96% accuracy.
The model is small and training on a MacBook Air M3 takes ~ 5 minutes.
▪Github
https://t.me/DataScienceT✅️
If you're looking for something to do this weekend and want to do a little reading and coding, here's the latest chapter from the book Build an LLM from Scratch , on setting up a GPT model to classify SPAM messages with up to 96% accuracy.
The model is small and training on a MacBook Air M3 takes ~ 5 minutes.
▪Github
https://t.me/DataScienceT
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⚡️ LLaVA-NeXT: A Strong Zero-shot Video Understanding Model
LLaVA-NeXT is one of the most powerful open source video understanding models available today, superior to all existing VLMs.
New SoTA!
LLaVA-Next demonstrates high data transfer rates and demonstrates excellent results in zero-shot training.
▪ Github: https://github.com/LLaVA-VL/LLaVA-NeXT
▪ Blog: https://llava-vl.github.io/blog/2024-04-30-llava-next-video/
▪ HF: https://huggingface.co/shi-labs/CuMo-mistral-7b
▪ Dataset: https://huggingface.co/datasets/shi-labs/CuMo_dataset
https://t.me/DataScienceT✅️
LLaVA-NeXT is one of the most powerful open source video understanding models available today, superior to all existing VLMs.
New SoTA!
LLaVA-Next demonstrates high data transfer rates and demonstrates excellent results in zero-shot training.
git clone https://github.com/LLaVA-VL/LLaVA-NeXT
▪ Github: https://github.com/LLaVA-VL/LLaVA-NeXT
▪ Blog: https://llava-vl.github.io/blog/2024-04-30-llava-next-video/
▪ HF: https://huggingface.co/shi-labs/CuMo-mistral-7b
▪ Dataset: https://huggingface.co/datasets/shi-labs/CuMo_dataset
https://t.me/DataScienceT
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MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels
🖥 Github: https://github.com/microsoft/ms-marco-web-search
📕 Paper: https://arxiv.org/abs/2405.07526v1
✅️ https://t.me/DataScienceT ✅️
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Forwarded from Machine Learning with Python
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Supports speech synthesis, different modes and an extensible (function call) plugin system.
Allows one-click deployment of private chat application OpenAI ChatGPT/Claude/Gemini/Groq/Ollama.
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