Function calling with Llama2? In our first addition to langchain_experimental, we're excited to integrate with llamaapi LlamaAPI is a hosted version of llama2 that adds in support for `functions` in the same way @OpenAI does Thanks to @edreisMD
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LLMS
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LlamaAPI Adds Function Calling Support to Llama2
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GPT Implementation: Attention Mechanism Deep Dive with Karpathy
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The best you can do is watch GPT from scratch by Karpathy. Great video! It’s more like an implementation of attention is all you need with a few changes in where layer norm is applied.
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FLASK: Fine-Grained LLM Evaluation Framework for Alignment Skills
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10/ FLASK – proposes fine-grained evaluation for LLMs based on a range of alignment skill sets; involves 12 skills and can help to provide a holistic view of a model’s performance depending on skill, domain, and level of difficulty.
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Retentive Network: Foundation Architecture Improving LLM Training Efficiency
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7/ Retentive Network – a foundation architecture for LLMs to improve training efficiency and inference; adapts retention mechanism for sequence modeling that support parallel representation, recurrent representations & chunkwise recurrent representation.
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Meta-Transformer: Unified Learning Across 12 AI Modalities
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8/ Meta-Transformer – performs unified learning across 12 modalities; supports tasks like fundamental perception (text, image, point cloud, audio, video), application (X-Ray, infrared, hyperspectral, & IMU), and data mining (graph, tabular, & time-series)
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Training Dense Retrievers for LLM In-Context Examples
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9/ Retrieve In-Context Example for LLMs – presents a framework to iteratively train dense retrievers to identify high-quality in-context examples for LLMs.
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LLM Challenges: Brittleness, Evaluation, and Experimental Design
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6/ Challenges & Application of LLMs – summarizes a comprehensive list of challenges when working with LLMs that range from brittle evaluations to prompt brittleness to a lack of robust experimental designs.
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Top ML Papers Week: Llama 2, FlashAttention-2, Retentive Networks
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Top ML Papers of the Week (July 17 – July 23): – Llama 2
– FlashAttention-2
– Meta-Transformer
– Retentive Network
– Challenges & Application of LLMs
– How is ChatGPT’s Behavior Changing Over Time?
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Meta releases Llama 2 foundation models from 7B to 70B parameters
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1/ Llama 2 – a collection of pretrained foundational models and fine-tuned chat models ranging in scale from 7B to 70B; Llama 2-Chat is competitive on a range of tasks and shows strong results on safety and helpfulness.
