Data Science | Machine Learning with Python for Researchers
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The Data Science and Python channel is for researchers and advanced programmers

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🦍 Gorilla: Large Language Model Connected with Massive APIs

Gorilla a finetuned LLaMA-based model that surpasses the performance of GPT-4 on writing API calls.

πŸ–₯ Github: https://github.com/ShishirPatil/gorilla

πŸ“• Paper: https://arxiv.org/abs/2305.15334

πŸ”— Demo: https://drive.google.com/file/d/1E0k5mG1mTiaz0kukyK1PdeohJipTFh6j/view?usp=share_link

πŸ‘‰ Project: https://shishirpatil.github.io/gorilla/

⭐️ Colab: https://colab.research.google.com/drive/1DEBPsccVLF_aUnmD0FwPeHFrtdC0QIUP?usp=sharing

https://t.iss.one/DataScienceT
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Segment Anything 3D

SAM-3D: A toolbox transfers 2D SAM segments into 3D scene-level point clouds.

πŸ–₯ Github: https://github.com/pointcept/segmentanything3d

⏩ Paper: https://arxiv.org/abs/2306.03908v1

πŸ“Œ Dataset: https://paperswithcode.com/dataset/scannet

https://t.iss.one/DataScienceT
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🐼 PandaLM: ReProducible and Automated Language Model Assessment

Judge large language model, named PandaLM, which is trained to distinguish the superior model given several LLMs. PandaLM's focus extends beyond just the objective correctness of responses, which is the main focus of traditional evaluation datasets.

πŸ–₯ Github: https://github.com/weopenml/pandalm

πŸ“• Paper: https://arxiv.org/abs/2306.05087v1

πŸ”— Dataset: https://github.com/tatsu-lab/stanford_alpaca#data-release

https://t.iss.one/DataScienceT
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πŸ“Ή Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

LLaMA is working on empowering large language models with video and audio understanding capability.

πŸ–₯ Github: https://github.com/damo-nlp-sg/video-llama

πŸ“• Paper: https://arxiv.org/abs/2306.02858

⏩ Demo: https://huggingface.co/spaces/DAMO-NLP-SG/Video-LLaMA

πŸ“Œ Model: https://modelscope.cn/studios/damo/video-llama/summary

https://t.iss.one/DataScienceT
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πŸ”οΈ Large Language Model for Geoscience

We introduce K2 (7B), an open-source language model trained by firstly further pretraining LLaMA on collected and cleaned geoscience literature, including geoscience open-access papers and Wikipedia pages, and secondly fine-tuning with knowledge-intensive instruction tuning data (GeoSignal).

git clone https://github.com/davendw49/k2.git
cd k2
conda env create -f k2.yml
conda activate k2


πŸ–₯ Github: https://github.com/davendw49/k2

⭐️ Demo: https://huggingface.co/daven3/k2_fp_delta

πŸ“• Paper: https://arxiv.org/abs/2306.05064v1

πŸ”— Dataset: https://huggingface.co/datasets/daven3/geosignal

https://t.iss.one/DataScienceT
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πŸ’² FinGPT: Open-Source Financial Large Language Models

Unlike proprietary models, FinGPT takes a data-centric approach, providing researchers and practitioners with accessible and transparent resources to develop their FinLLMs.

πŸ–₯ Github: https://github.com/ai4finance-foundation/fingpt

⭐️ FinNLP: https://github.com/ai4finance-foundation/finnlp

πŸ“• Paper: https://arxiv.org/abs/2306.06031v1

πŸ”— Project: https://ai4finance-foundation.github.io/FinNLP/

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πŸ§” 4DHumans: Reconstructing and Tracking Humans with Transformers

Fully "transformerized" version of a network for human mesh recovery.

πŸ–₯ Github: https://github.com/shubham-goel/4D-Humans

⭐️ Colab: https://colab.research.google.com/drive/1Ex4gE5v1bPR3evfhtG7sDHxQGsWwNwby?usp=sharing

πŸ“• Paper: https://arxiv.org/pdf/2305.20091.pdf

πŸ”— Project: https://shubham-goel.github.io/4dhumans/

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πŸ”₯ Scalable Diffusion Models with Transformers (DiT)

git clone https://github.com/facebookresearch/DiT.git

πŸ–₯ Github: https://github.com/facebookresearch/DiT

πŸ–₯ Colab: https://colab.research.google.com/github/facebookresearch/DiT/blob/main/run_DiT.ipynb

⭐️ Project: https://www.wpeebles.com/DiT

⏩ Paprer: https://arxiv.org/abs/2212.09748

βœ”οΈ Dataset: https://paperswithcode.com/dataset/imagenet

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Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement
at 100k Steps-Per-Second

πŸ–₯ Github: https://github.com/facebookresearch/galactic

⏩ Paper: https://arxiv.org/pdf/2306.07552v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/vizdoom

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Macaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text Integration

Macaw-LLM is a model of its kind, bringing together state-of-the-art models for processing visual, auditory, and textual information, namely CLIP, Whisper, and LLaMA.

πŸ–₯ Github: https://github.com/lyuchenyang/macaw-llm

⭐️ Model: https://tinyurl.com/yem9m4nf

πŸ“• Paper: https://tinyurl.com/4rsexudv

πŸ”— Dataset: https://github.com/lyuchenyang/Macaw-LLM/blob/main/data

https://t.iss.one/DataScienceT
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