Agents: An Open-source Framework for Autonomous Language Agents Zhou et al.: https://
arxiv.org/abs/2309.07870 #ArtificialIntelligence #DeepLearning #MachineLearning
OPEN SOURCE
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Open-source Framework for Autonomous Language Agents
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Interactive Virtual Panel on LLMs: Open-source vs Commercial Solutions
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Don't miss our interactive virtual panel with #LLM experts from @llama_index
, Bank of America & @predibase Topics: Open-source vs. commercial LLMs High-value use cases Tips for customization (#RAG, #finetuning) Overcoming common pitfalls https://
pbase.ai/3PDq4Qz -
Training YOLOv8 for Real-Time Pothole Detection: Model Comparison
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🚀YOLOv8 is one of the fastest and most accurate YOLO models out there.https://t.co/l9JUDdcJkD
— Satya Mallick (@LearnOpenCV) 14 septembre 2023
Why not leverage it for training a real-world dataset? Let's train YOLOv8 to detect potholes in real time and compare performance between three different YOLOv8 models.… pic.twitter.com/IocN7SXl5eYOLOv8 is one of the fastest and most accurate YOLO models out there. https://
learnopencv.com/train-yolov8-o
n-custom-dataset/
… Why not leverage it for training a real-world dataset? Let's train YOLOv8 to detect potholes in real time and compare performance between three different YOLOv8 models. -
Llama 2 and Code Llama Models Now Available on Kaggle
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Llama 2 and Code Llama are now on #KaggleModels!
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Kaggle Community Ready to Build with Llama 2
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We can't wait for the Kaggle community to start building with Llama 2!
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Open LLM Leaderboard benchmarks collection launched
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If you find this work interesting, please join our Discord channel to ask questions and discuss. https://
discord.gg/8z2Pe7cpRv Also, thank you to @Thom_Wolf for help on setting up the leaderboard at: The Big Benchmarks Collection: https://
huggingface.co/collections/op
en-llm-leaderboard/the-big-benchmarks-collection-64faca6335a7fc7d4ffe974a
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Open-Source LLMs Become Effective Tool Manipulators
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Find the paper on @arxiv at https://
arxiv.org/abs/2305.16504 and more details on our blog at https://
sambanova.ai/blog/enabling-
open-source-llms-to-become-effective-tool-manipulators/
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Open-Source LLMs Struggle With API Selection and Code Generation
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According to our error analysis, we observe that open-source LLMs often face difficulty in 1. API selection
2. API argument population,
3. generating legitimate and executable code. (6/10) -
OSS Models Close Gap With Proprietary Tools via Techniques
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As seen on the @huggingface leaderboard, these techniques reduce the gap between proprietary and OSS models significantly and make OSS models useful for tool manipulation. https://
huggingface.co/spaces/qianton
g-xu/toolbench-leaderboard
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Optimizing OSS Models with System Prompts RAG Fine-tuning
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We use established fast and simple techniques to improve OSS model performance. These techniques include system prompts to generate less verbose answers, RAG to reduce hallucinations and fine-tuning to improve accuracy. (7/10)