4/ Introduction to Vision-Language Modeling – presents an introduction to vision-language models along with key details of how they work and how to effectively train these models.
LLMS
-
Top ML Papers of the Week: SimPO, GNN-RAG, and More
By
–
The Top ML Papers of the Week (May 27 – June 2): – SimPO
– GNN-RAG
– Attention as an RNN
– Abacus Embeddings
– Symbolic Chain-of-Thought
– Contextual Position Encoding
… -
Contextual Position Encoding: New Method for Transformer Models
By
–
1/ Contextual Position Encoding – proposes a new position encoding method, CoPE, to enable the position to be conditioned on context by incrementing position only on certain tokens…
-
Solar-1-mini-chat-ja: Compact Japanese LLM Model
By
–
#solarllmja is registered at #awesome_japanese_llm, https://
github.com/llm-jp/awesome
-japanese-llm
…. If you have any service in Japan , please checkout `solar-1-mini-chat-ja` at https://
console.upstage.ai. It's small but very string in Japanese! -
LLM Fine-tuning and Model Merging for Cost-Effective Adaptation
By
–
“Training LLMs from scratch costs $ millions in compute. But LLMs can cheaply be adapted to new tasks via fine-tuning, leading to a proliferation of models that suit specific use cases. Fine-tuned models can be rapidly merged to combine capabilities and generalize to new skills.”
-
What is Deep Learning and Artificial Intelligence Explained
By
–
What is Deep Learning and Artificial Intelligence? #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
geni.us/What-is-A-I -
PAQ8 bit sequences language models efficiency 2010
By
–
I agree, but it’s tricky for models to learn this. It would make a good PhD thesis Curiously, the old PAQ8 language models back in 2010 used sequences of bits, as you suggest, because we had to rely on binary C operations to make them efficient enough. See
-
GPT and Generative AI: Exploring LLMs and Advanced Technologies
By
–
GPT & Generative AI and LLMs! @DataSciConnect #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #Books #100DaysofCode https://
geni.us/Align-AI-Summi
ts
… -
Generative AI and LLMs Summit: GPT Technology and Machine Learning
By
–
GPT & Generative AI and LLMs! @DataSciConnect #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #Books #100DaysofCode https://
geni.us/Align-AI-Summi
ts
… -
Continuous Vectors vs Large-Scale Quantisation in AI Models
By
–
I strongly agree with all your comments. Thanks for sharing. One question: if researchers figure out how to do continuous vectors, do you think that will be better than large-scale (or residual) quantisation? Why?