• Integrating experiment tracking tools like Weights & Biases (WandB)
• Implementing evaluation engines to test model performance against benchmarks MonsterAPIs provides interactive GUI and set of APIs to launch an fine-tuning job on custom datasets in your niche use-cases.
LLMS
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MonsterAPIs: Interactive Fine-tuning Platform with WandB Integration
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GPU Configuration and Memory Optimization for Model Fine-tuning
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The process of fine-tuning and evaluation involves several technical challenges: • Configuring GPU computing environments
• Optimising memory usage and finding the optimal batch size
• Setting up model configurations for specific requirements -
Fine-tuning Open Source LLMs with MonsterAPI Evaluation
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Evaluation of fine-tuning LLMs using MonsterAPI Find out a new blog on how you can use @monsterapis for fine-tuning state-of-the-art open source LLMs and evaluate on benchmarks evaluation metrics such as MMLU, gsm8k, etc. Learn more below:
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Technical analysis of Perplexity’s search index and crawler architecture
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Building a search index is quite tricky – there are only 3 indexes I am aware of – Bing, Google and Brave where Brave was also relying on Bing for 5% of queries initially. They rather do the same thing that Perplexity does here – a combo of a search index and a crawler on top
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Efficient scaling: training compute versus inference compute gains
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I'd be interested too but I don't expect much. Still a cool approach, with lots of potential gains in scaling more efficiently (training compute =>> inference compute)
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Tele-FLM-1T: Progressive Training and Depth Growth Techniques
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Here are the juicy lessons from the 1T model Tele-FLM-1T: – Trained progressively in 3 stages: 52B -> 102B -> 1T parameters on ~2T tokens – Depth growth technique: selects layers to duplicate based on their input-output distance metrics, prioritizing middle layers with smaller
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Limitations of current AI web search and real-time data
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Nope, current web search doesn't work with real-time data
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Llama 3.1 Becomes Number One Trending Model on Hugging Face
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llama 3.1 by @AIatMeta is now #1 trending model on Hugging Face! https://
huggingface.co/models -
Technical analysis of SearchGPT image understanding capabilities
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For SearchGPT it is unclear – but it should be able to natively understand images w/o using a vision model
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SearchGPT Architecture: Multimodal Capabilities and Bing Search Integration
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It seems that SearchGPT may be powered by a proper image multimodality + In case you were in doubt – it is still using Bing search index