[2302.14045] Language Is Not All You Need: Aligning Perception with Language Models
https://arxiv.org/abs/2302.14045
#paper New generation
https://arxiv.org/abs/2302.14045
#paper New generation
https://arxiv.org/abs/2207.06881 #Paper Recurrent Memory Transformer. Scaling transformer architecture to long sequences.
https://www.deepmind.com/blog/rt-2-new-model-translates-vision-and-language-into-action
New model translates vision and language into action based on LLM
New model translates vision and language into action based on LLM
Google DeepMind
RT-2: New model translates vision and language into action
Introducing Robotic Transformer 2 (RT-2), a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for...
https://www.anyscale.com/blog/continuous-batching-llm-inference
LLM inference acceleration #Frameworks
LLM inference acceleration #Frameworks
Anyscale
Achieve 23x LLM Inference Throughput & Reduce p50 Latency
In this blog, we discuss continuous batching, a critical systems-level optimization that improves both throughput and latency under load for LLMs.
❤1
Medium
Goodbye databases, it’s time to embrace Vector Databases!
The AI revolution is reshaping industries, promising remarkable innovations while introducing new challenges. In this transformative…
https://codemaker2016.medium.com/goodbye-databases-its-time-to-embrace-vector-databases-0ffa7879980e
#Tips
#Tips
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https://huggingface.co/collections/osanseviero/model-merging-65097893623330a3a51ead66
Model Merging: papers
#Paper
Model Merging: papers
#Paper
huggingface.co
Model Merging - a osanseviero Collection
Model Merging is a very popular technique nowadays in LLM. Here is a chronological list of papers on the space that will help you get started with it!
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https://github.com/SeldonIO/alibi-detect Algorithms for outlier, adversarial and drift detection
https://github.com/SeldonIO/alibi Algorithms for explaining machine learning models
#Frameworks #library #anomaly #drift
https://github.com/SeldonIO/alibi Algorithms for explaining machine learning models
#Frameworks #library #anomaly #drift
GitHub
GitHub - SeldonIO/alibi-detect: Algorithms for outlier, adversarial and drift detection
Algorithms for outlier, adversarial and drift detection - SeldonIO/alibi-detect
Grokking:
1. Fist paper: https://arxiv.org/abs/2201.02177
2. Transformers: https://arxiv.org/pdf/2405.15071
3. Simple framework: https://arxiv.org/pdf/2405.20233
1. Fist paper: https://arxiv.org/abs/2201.02177
2. Transformers: https://arxiv.org/pdf/2405.15071
3. Simple framework: https://arxiv.org/pdf/2405.20233
arXiv.org
Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets
In this paper we propose to study generalization of neural networks on small algorithmically generated datasets. In this setting, questions about data efficiency, memorization, generalization, and...
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and many other libraries.
https://mars-project.readthedocs.io/
#Frameworks
https://mars-project.readthedocs.io/
#Frameworks
Tutorial: Scalable and Distributed ML Workflows with DVC and Ray
Part 1: https://dvc.ai/blog/dvc-ray
Part 2: https://dvc.ai/blog/dvc-ray-part-2
Part 1: https://dvc.ai/blog/dvc-ray
Part 2: https://dvc.ai/blog/dvc-ray-part-2
DVC AI
Tutorial: Scalable and Distributed ML Workflows with DVC and Ray (Part 1)
This tutorial introduces you to integrating DVC (Data Version Control) with Ray, turning them into your go-to toolkit for creating automated, scalable, and distributed ML pipelines.
https://web.stanford.edu/~jurafsky/slp3/
#books Speech and Language Processing (3rd ed. draft)
Dan Jurafsky and James H. Martin
#books Speech and Language Processing (3rd ed. draft)
Dan Jurafsky and James H. Martin