Note that different tokenizers (the step where you transform words into understandable numbers for the model) influence their sentence comprehension, too!
LLMS
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Open-Orca Fine-Tune Model Inference Implementation
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It's an open-orca fine-tune https://
kaggle.com/code/ybabakhin
/1st-place-single-model-inference
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Hugging Face Launches Free Deep Reinforcement Learning Course
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Welcome to the Deep Reinforcement Learning Course – Hugging Face Deep RL Course https://
bit.ly/3PMaByU #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Winning Kaggle Science QA Competition with 7B Model
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In the recent Kaggle science QA competition the winning model was a 7B 😀
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Collama: Wikipedia-Style Crowd-Sourced LLM Fine-Tuning
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Collama: a quick implementation of the idea of Wikipedia-style crowd-sourced fine-tuning for LLMs.
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Google Gemini Outperforms GPT-4 by 5X, GPU Requirements
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Google Gemini Eats The World – Gemini Smashes GPT-4 By 5X, The GPU-Poors https://
bit.ly/3PcLUtK
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
LoRA Exchange LoRAX Serve Hundreds Fine-Tuned LLMs Cost
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Link to the blog: https://
predibase.com/blog/lora-exch
ange-lorax-serve-100s-of-fine-tuned-llms-for-the-cost-of-one
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LoRAX: Serve Hundreds Fine-Tuned Models Single GPU
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Serving multiple #finetuned models typically requires dedicated, costly GPUs for each deployment—until now. Introducing LoRA Exchange (LoRAX): dynamically serve 100s of fine-tuned #LLMs on a single GPU w/out sacrificing throughput at a much lower cost.
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Master LLMs: Valuable Tips and Insights Video Guide
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For further insights and valuable tips on how to master LLMs to your favor, be sure to check out this video: https://
youtu.be/fylqJ3E4mwQ -
Retrieval Augmented Generation: Improving Model Accuracy and Safety
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Lastly, if you're still experiencing issues related to answer accuracy, hallucinations or outdated documentation, consider using Retrieval Augmented Generations. These can make your model responses safer and more attuned to your needs.