Curious how different this is from function calls as I know a lot of people were using them for just the JSON output
LLMS
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Idefics3: State-of-the-Art Vision+Text Model Released
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Llama 3.1 multimodal is not released yet? We got you covered with the new Idefics3 a state of the art Vision+Text model based on the latest Llama 3.1
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Optimizing Databricks LLM Pipelines with DSPy
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Optimizing Databricks LLM Pipelines with DSPy https://
bit.ly/3zzJfq3
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
GPT-4 Training Energy Consumption Versus Netflix Streaming Hours
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"it’s estimated that GPT-4 consumed between 51,773 MWh and 62,319 MWh" [1] "streaming an hour of Netflix requires around 0.8 kWh (0.0008 MWh) of electricity." [2] Es decir, entrenar a GPT-4 (tomando el valor superior) cuesta unas ~78M horas de Netflix. Es decir, el costo
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Figure 02 Humanoid Robot Introduces Natural Language Conversations
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Introducing Figure 02, a humanoid robot capable of natural language conversations thanks to OpenAI. What do you think? pic.twitter.com/C85gy8v9J6
— MIT CSAIL (@MIT_CSAIL) 6 août 2024Introducing Figure 02, a humanoid robot capable of natural language conversations thanks to OpenAI. What do you think?
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Mistral Large 2 Excels in Coding, Math, and Hard Prompts
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Mistral Large 2 (2407) is now on @lmsysorg
. It performs extremely well in the Coding, Hard Prompts, Math, and Longer Query categories, where it outperforms GPT4-Turbo and Claude 3 Opus. It is also doing very well in Instruction Following where it ranks above Llama 3.1 405B. -
Whisper Model Customization for Air Traffic Control Safety
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Enhance Speech Recognition in Air Traffic Control with Whisper. We've tailored OpenAI's powerful Whisper model to better understand the unique challenges of air traffic communications.
— Satya Mallick (@LearnOpenCV) 6 août 2024
Discover how customizing Whisper can improve safety and accuracy, with insights into our… pic.twitter.com/pMERB815ziEnhance Speech Recognition in Air Traffic Control with Whisper. We've tailored OpenAI's powerful Whisper model to better understand the unique challenges of air traffic communications. Discover how customizing Whisper can improve safety and accuracy, with insights into our
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LM-Evaluation-Harness Aggregation Error Analysis
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The funniest part is that manually averaging your scores doesn't give you the same result as lm-evaluation-harness's aggregation (~0.01% error).
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Experimenting with Model Merging and Quantization Techniques
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Anyway, have fun quantizing and running this monster! This is a silly experiment but who knows, we might: 1/ Realize it's good at something, like creative writing
2/ Get some insights into how to create these self-merges Good luck everyone and make your own frankenmerges