🔥 Llama 2: Open Foundation and Fine-Tuned Chat Models
Llama 2 collection of pretrained and fine-tuned large language models (LLMs).
🖥 Github: https://github.com/facebookresearch/llama
⭐️ Demo: https://huggingface.co/blog/llama2
🤗Hugging face: https://huggingface.co/meta-llama/Llama-2-70b
📕 Paper: https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/
https://t.iss.one/DataScienceT
Llama 2 collection of pretrained and fine-tuned large language models (LLMs).
🖥 Github: https://github.com/facebookresearch/llama
⭐️ Demo: https://huggingface.co/blog/llama2
🤗Hugging face: https://huggingface.co/meta-llama/Llama-2-70b
📕 Paper: https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/
https://t.iss.one/DataScienceT
👍5😍1
SVDFormer: Complementing Point Cloud via Self-view Augmentation and Self-structure Dual-generator
🖥 Github: https://github.com/czvvd/svdformer
⏩ Paper: https://arxiv.org/pdf/2307.08492v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/shapenet
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/czvvd/svdformer
⏩ Paper: https://arxiv.org/pdf/2307.08492v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/shapenet
https://t.iss.one/DataScienceT
👍4
🌆Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback
🖥 Github: https://github.com/tetrzim/diffusion-human-feedback
⏩ Paper: https://arxiv.org/pdf/2307.02770v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/imagenet
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/tetrzim/diffusion-human-feedback
⏩ Paper: https://arxiv.org/pdf/2307.02770v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/imagenet
https://t.iss.one/DataScienceT
❤4👍2
FLASK: Fine-grained Language Model Evaluation Based on Alignment Skill Sets
🖥 Github: https://github.com/kaistai/flask
⏩ Paper: https://arxiv.org/pdf/2307.10928v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/gsm8k
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/kaistai/flask
⏩ Paper: https://arxiv.org/pdf/2307.10928v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/gsm8k
https://t.iss.one/DataScienceT
❤4
Forwarded from Python | Machine Learning | Coding | R
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🐋 FreeWilly, Large And Mighty Instruction Fine-Tuned Models
.
FreeWilly1 and FreeWilly2 set a new standard in the field of open access Large Language Models.
⭐️ Post: https://stability.ai/blog/freewilly-large-instruction-fine-tuned-models
📌 FreeWilly1: https://huggingface.co/stabilityai/FreeWilly1-Delta-SafeTensor
📌 FreeWilly2: https://huggingface.co/stabilityai/FreeWilly1-Delta-SafeTensor
https://t.iss.one/DataScienceT
.
FreeWilly1 and FreeWilly2 set a new standard in the field of open access Large Language Models.
⭐️ Post: https://stability.ai/blog/freewilly-large-instruction-fine-tuned-models
📌 FreeWilly1: https://huggingface.co/stabilityai/FreeWilly1-Delta-SafeTensor
📌 FreeWilly2: https://huggingface.co/stabilityai/FreeWilly1-Delta-SafeTensor
https://t.iss.one/DataScienceT
👍3❤1
↗️ L-Eval: Instituting Standardized Evaluation for Long Context Language Models
Data and code for L-Eval, a comprehensive long context language models evaluation benchmark.
🖥 Github: https://github.com/bshall/urhythmic
🧑💻Model: https://huggingface.co/datasets/L4NLP/LEval
📕 Paper: https://arxiv.org/abs/2307.11088
🚀 Dataset: https://paperswithcode.com/dataset/quality
https://t.iss.one/DataScienceT
Data and code for L-Eval, a comprehensive long context language models evaluation benchmark.
🖥 Github: https://github.com/bshall/urhythmic
🧑💻Model: https://huggingface.co/datasets/L4NLP/LEval
📕 Paper: https://arxiv.org/abs/2307.11088
🚀 Dataset: https://paperswithcode.com/dataset/quality
https://t.iss.one/DataScienceT
👍3❤1
⭐️ CNOS: A Strong Baseline for CAD-based Novel Object Segmentation
Three-stage approach to segment unseen objects in RGB images using their CAD models.
🖥 Github: https://github.com/nv-nguyen/cnos
📕 Paper: https://arxiv.org/abs/2307.11067
🚀 Dataset: https://bop.felk.cvut.cz/datasets/
https://t.iss.one/DataScienceT
Three-stage approach to segment unseen objects in RGB images using their CAD models.
🖥 Github: https://github.com/nv-nguyen/cnos
📕 Paper: https://arxiv.org/abs/2307.11067
🚀 Dataset: https://bop.felk.cvut.cz/datasets/
https://t.iss.one/DataScienceT
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200 Udacity FREE Courses on Machine Learning and Data Science!
https://www.mltut.com/udacity-free-courses-on-machine-learning/
https://t.iss.one/CodeProgrammer
https://www.mltut.com/udacity-free-courses-on-machine-learning/
https://t.iss.one/CodeProgrammer
❤🔥3👍3🏆3
🗣 DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection and Instruction-Aware Models for Conversational AI.
🖥 Github: https://github.com/salesforce/DialogStudio
📕 Paper: https://arxiv.org/abs/2307.10172v2
🔥 Dataset: https://paperswithcode.com/dataset/dialogstudio
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/salesforce/DialogStudio
📕 Paper: https://arxiv.org/abs/2307.10172v2
🔥 Dataset: https://paperswithcode.com/dataset/dialogstudio
https://t.iss.one/DataScienceT
👍4❤2
Kaggle is one of the goto platforms for Machine Learning
Here's how to use it to it's maximum potential 💯
{ Explore Learn Section }
kaggle.com/learn
{ Explore Datasets }
kaggle.com/datasets
{ Explore Challenges}
kaggle.com/competitions
{ Learn By Building }
kaggle.com/code
{ Seek & Give Help }
kaggle.com/discussion
https://t.iss.one/DataScienceT
Here's how to use it to it's maximum potential 💯
{ Explore Learn Section }
kaggle.com/learn
{ Explore Datasets }
kaggle.com/datasets
{ Explore Challenges}
kaggle.com/competitions
{ Learn By Building }
kaggle.com/code
{ Seek & Give Help }
kaggle.com/discussion
https://t.iss.one/DataScienceT
👍10❤6
⏩ Edge Guided GANs with Multi-Scale Contrastive Learning for Semantic Image Synthesis
🖥 Github: https://github.com/ha0tang/ecgan
📕 Paper: https://arxiv.org/abs/2307.12084v1
🔥 Dataset: https://paperswithcode.com/dataset/cityscapes
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/ha0tang/ecgan
📕 Paper: https://arxiv.org/abs/2307.12084v1
🔥 Dataset: https://paperswithcode.com/dataset/cityscapes
https://t.iss.one/DataScienceT
Remote Bio-Sensing: Open Source Benchmark Framework for Fair Evaluation of rPPG
🖥 Github: https://github.com/remotebiosensing/rppg
📕 Paper: https://arxiv.org/abs/2307.12644v1
🔥 Dataset: https://paperswithcode.com/dataset/ubfc-rppg
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/remotebiosensing/rppg
📕 Paper: https://arxiv.org/abs/2307.12644v1
🔥 Dataset: https://paperswithcode.com/dataset/ubfc-rppg
https://t.iss.one/DataScienceT
👍5
TF-ICON: Diffusion-Based Training-Free Cross-Domain Image Composition (ICCV 2023)
🖥 Github: https://github.com/Shilin-LU/TF-ICON
📕 Paper: https://arxiv.org/abs/2307.12644v1
🔥 Dataset: https://paperswithcode.com/dataset/ubfc-rppg
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/Shilin-LU/TF-ICON
📕 Paper: https://arxiv.org/abs/2307.12644v1
🔥 Dataset: https://paperswithcode.com/dataset/ubfc-rppg
https://t.iss.one/DataScienceT
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