LLM_Fine_Tuning_Molecular_Properties
🖥 Github: https://github.com/SylwiaNowakowska/LLM_Fine_Tuning_Molecular_Properties
📕 Paper: https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/65030b55b338ec988a780108/original/chem-ber-ta-2-fine-tuning-for-molecule-s-hiv-replication-inhibition-prediction.pdf
🔥 Dataset: https://paperswithcode.com/dataset/moleculenet
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🖥 Github: https://github.com/SylwiaNowakowska/LLM_Fine_Tuning_Molecular_Properties
📕 Paper: https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/65030b55b338ec988a780108/original/chem-ber-ta-2-fine-tuning-for-molecule-s-hiv-replication-inhibition-prediction.pdf
🔥 Dataset: https://paperswithcode.com/dataset/moleculenet
https://news.1rj.ru/str/DataScienceT
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🦙 LLaVA: Large Language and Vision Assistant
🖥 Github: https://github.com/haotian-liu/LLaVA
📕 Paper: https://arxiv.org/pdf/2309.09958v1.pdf
⭐️ Datasets: https://paperswithcode.com/dataset/mmlu
https://news.1rj.ru/str/DataScienceT
git clone https://github.com/haotian-liu/LLaVA.git
cd LLaVA🖥 Github: https://github.com/haotian-liu/LLaVA
📕 Paper: https://arxiv.org/pdf/2309.09958v1.pdf
⭐️ Datasets: https://paperswithcode.com/dataset/mmlu
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LLMKE
🖥 Github: https://github.com/bohuizhang/llmke
📕 Paper: https://arxiv.org/pdf/2309.08491v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/lama
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/bohuizhang/llmke
📕 Paper: https://arxiv.org/pdf/2309.08491v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/lama
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⛓️🛠️ ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing
🖥 Github: https://github.com/ianarawjo/ChainForge
⭐️ Project: https://chainforge.ai
📕 Paper: https://arxiv.org/abs/2309.09128v1
https://news.1rj.ru/str/DataScienceT
pip install chainforge🖥 Github: https://github.com/ianarawjo/ChainForge
⭐️ Project: https://chainforge.ai
📕 Paper: https://arxiv.org/abs/2309.09128v1
https://news.1rj.ru/str/DataScienceT
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😠 GPTFUZZER : Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts
Fuzzer maintains over 90% attack success rate against ChatGPT and Llama-2 models.
🖥 Github: https://github.com/sherdencooper/gptfuzz
📕 Paper: https://arxiv.org/abs/2309.10253v1
⏩ Dataset: https://sites.google.com/view/llm-jailbreak-study
https://news.1rj.ru/str/DataScienceT
Fuzzer maintains over 90% attack success rate against ChatGPT and Llama-2 models.
🖥 Github: https://github.com/sherdencooper/gptfuzz
📕 Paper: https://arxiv.org/abs/2309.10253v1
⏩ Dataset: https://sites.google.com/view/llm-jailbreak-study
https://news.1rj.ru/str/DataScienceT
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Distillation-in-dg
🖥 Github: https://github.com/vorobeevich/distillation-in-dg
📕 Paper: https://arxiv.org/pdf/2309.11446v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/office-home
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/vorobeevich/distillation-in-dg
📕 Paper: https://arxiv.org/pdf/2309.11446v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/office-home
https://news.1rj.ru/str/DataScienceT
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📊 PAMS: Platform for Artificial Market Simulations
Artificial market simulation is a multi-agent simulation and run virtual markets on your computer.
🖥 Github: https://github.com/masanorihirano/pams
📕 Paper: https://arxiv.org/abs/2309.10729v1
⏩ Docs: https://pams.hirano.dev/
https://news.1rj.ru/str/DataScienceT
Artificial market simulation is a multi-agent simulation and run virtual markets on your computer.
$ pip install pams🖥 Github: https://github.com/masanorihirano/pams
📕 Paper: https://arxiv.org/abs/2309.10729v1
⏩ Docs: https://pams.hirano.dev/
https://news.1rj.ru/str/DataScienceT
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LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
🖥 Github: https://github.com/dvlab-research/longlora
📕 Paper: https://arxiv.org/pdf/2309.12307v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/pg-19
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/dvlab-research/longlora
📕 Paper: https://arxiv.org/pdf/2309.12307v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/pg-19
https://news.1rj.ru/str/DataScienceT
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🎓 BayesDLL: Bayesian Deep Learning Library
New Bayesian neural network library for PyTorch for large-scale deep network
🖥 Github: https://github.com/samsunglabs/bayesdll
📕 Paper: https://arxiv.org/abs/2309.12928v1
⭐️ Dataset: https://paperswithcode.com/dataset/oxford-102-flower
https://news.1rj.ru/str/DataScienceT
New Bayesian neural network library for PyTorch for large-scale deep network
🖥 Github: https://github.com/samsunglabs/bayesdll
📕 Paper: https://arxiv.org/abs/2309.12928v1
⭐️ Dataset: https://paperswithcode.com/dataset/oxford-102-flower
https://news.1rj.ru/str/DataScienceT
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🔊 Listen, Think, and Understand
AI model that has both audio perception and a reasoning ability
🖥 Github: https://github.com/YuanGongND/ltu
☑️ Demo: https://18c618fc8f07ec494e.gradio.live/
📕 Paper: https://arxiv.org/abs/2309.14405v1
🤗 HH: https://huggingface.co/spaces/yuangongfdu/ltu-2
⭐️ Dataset: https://paperswithcode.com/dataset/iemocap
https://news.1rj.ru/str/DataScienceT
AI model that has both audio perception and a reasoning ability
🖥 Github: https://github.com/YuanGongND/ltu
☑️ Demo: https://18c618fc8f07ec494e.gradio.live/
📕 Paper: https://arxiv.org/abs/2309.14405v1
🤗 HH: https://huggingface.co/spaces/yuangongfdu/ltu-2
⭐️ Dataset: https://paperswithcode.com/dataset/iemocap
https://news.1rj.ru/str/DataScienceT
➕ fastMONAI: A low-code deep learning library for medical image analysis
Simplifying deep learning for medical imaging.
🖥 Github: https://github.com/MMIV-ML/fastMONAI
Project: https://fastmonai.no
📕 Paper: https://www.sciencedirect.com/science/article/pii/S2665963823001203
🖥 Colab: https://colab.research.google.com/github/MMIV-ML/fastMONAI/blob/master/nbs/10a_tutorial_classification.ipynb
https://news.1rj.ru/str/DataScienceT
Simplifying deep learning for medical imaging.
git clone https://github.com/MMIV-ML/fastMONAI🖥 Github: https://github.com/MMIV-ML/fastMONAI
Project: https://fastmonai.no
📕 Paper: https://www.sciencedirect.com/science/article/pii/S2665963823001203
🖥 Colab: https://colab.research.google.com/github/MMIV-ML/fastMONAI/blob/master/nbs/10a_tutorial_classification.ipynb
https://news.1rj.ru/str/DataScienceT
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⭐️Scenimefy: Learning to Craft Anime Scene via Semi-Supervised Image-to-Image Translation
🖥 Github: https://github.com/Yuxinn-J/Scenimefy/tree/main
☑️ Demo: https://huggingface.co/spaces/YuxinJ/Scenimefy
📕 Paper: https://arxiv.org/abs/2308.12968
⏩Project: https://yuxinn-j.github.io/projects/Scenimefy.html
⭐️ Dataset: https://github.com/Yuxinn-J/Scenimefy/tree/main#open_file_folder-anime-scene-dataset
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git clone https://github.com/Yuxinn-J/Scenimefy.git🖥 Github: https://github.com/Yuxinn-J/Scenimefy/tree/main
☑️ Demo: https://huggingface.co/spaces/YuxinJ/Scenimefy
📕 Paper: https://arxiv.org/abs/2308.12968
⏩Project: https://yuxinn-j.github.io/projects/Scenimefy.html
⭐️ Dataset: https://github.com/Yuxinn-J/Scenimefy/tree/main#open_file_folder-anime-scene-dataset
https://news.1rj.ru/str/DataScienceT
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