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And we’re not going to stop here – stay tuned as we enable more experiences to build AI with open models on Google Cloud!"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"Read the full post at ","raw":"Read the full post at "},{"type":"link","href":"https://huggingface.co/blog/llama31-on-vertex-ai","raw":"https://huggingface.co/blog/llama31-on-vertex-ai"}],"rawContent":"🤗 Serving Meta Llama 3.1 405B on Google Cloud is now possible via the Hugging Face Deep Learning Containers (DLCs) for Text Generation Inference (TGI)\n\nIn this post, we showcase how to deploy https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct-FP8 on an A3 instance with 8 x H100 GPUs on Vertex AI\n\nThanks to the Hugging Face DLCs for TGI and Google Cloud Vertex AI, deploying a high-performance text generation container for serving Large Language Models (LLMs) has never been easier. 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and Claude 3 Opus scores when evaluating LMs","raw":"🔝Surpasses the former version of Prometheus, and has a high correlation with human, GPT-4, and Claude 3 Opus scores when evaluating LMs"},{"type":"new_line","raw":"\n"},{"type":"text","value":"📝Apache 2.0 license","raw":"📝Apache 2.0 license"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"Long-story short, an amazing job from Kaist AI bridging the gap with LLM evaluators other than proprietary and bigger models!","raw":"Long-story short, an amazing job from Kaist AI bridging the gap with LLM evaluators other than proprietary and bigger models!"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"This week at Argilla, we decided to add a new task to use Prometheus 2 as an LLM evaluator using ","raw":"This week at Argilla, we decided to add a new task to use Prometheus 2 as an LLM evaluator using "},{"type":"inline_code","code":"distilabel","raw":"`distilabel`"},{"type":"text","value":", so we implemented ","raw":", so we implemented "},{"type":"inline_code","code":"PrometheusEval","raw":"`PrometheusEval`"},{"type":"text","value":".","raw":"."},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"😱 Using ","raw":"😱 Using "},{"type":"inline_code","code":"PrometheusEval","raw":"`PrometheusEval`"},{"type":"text","value":" running their 7B variant with vLLM in a single L40 on top of ","raw":" running their 7B variant with vLLM in a single L40 on top of "},{"type":"resource","resource":{"type":"dataset","id":"HuggingFaceH4/instruction-dataset"},"url":"https://huggingface.co/datasets/HuggingFaceH4/instruction-dataset","raw":"https://huggingface.co/datasets/HuggingFaceH4/instruction-dataset"},{"type":"text","value":", we got the 327 existing prompt-completion pairs evaluated and pushed to the Hub in less than 2 minutes!","raw":", we got the 327 existing prompt-completion pairs evaluated and pushed to the Hub in less than 2 minutes!"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"Find the generated dataset and the code at ","raw":"Find the generated dataset and the code at "},{"type":"resource","resource":{"type":"dataset","id":"distilabel-internal-testing/instruction-dataset-prometheus"},"url":"https://huggingface.co/datasets/distilabel-internal-testing/instruction-dataset-prometheus","raw":"https://huggingface.co/datasets/distilabel-internal-testing/instruction-dataset-prometheus"}],"rawContent":"🔥 Prometheus 2 was recently released by Kaist AI as an alternative and closely mirroring both human and GPT-4 evaluation, and surpassing the former Prometheus!\n\nhttps://huggingface.co/prometheus-eval/prometheus-7b-v2.0\nhttps://huggingface.co/prometheus-eval/prometheus-8x7b-v2.0\n\n🌬️Fine-tuned on top of https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2 and https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1\n🗂️The datasets used for fine-tuning have been publicly released i.e. https://huggingface.co/datasets/prometheus-eval/Feedback-Collection and https://huggingface.co/datasets/prometheus-eval/Preference-Collection\n🤝🏻Unified LM evaluator for absolute (a single prompt-completion pair) and relative (two completions for a given prompt) due to model merging\n❌No longer needs a mandatory reference / golden answer, but can still be provided optionally\n🔝Surpasses the former version of Prometheus, and has a high correlation with human, GPT-4, and Claude 3 Opus scores when evaluating LMs\n📝Apache 2.0 license\n\nLong-story short, an amazing job from Kaist AI bridging the gap with LLM evaluators other than proprietary and bigger models!\n\nThis week at Argilla, we decided to add a new task to use Prometheus 2 as an LLM evaluator using `distilabel`, so we implemented `PrometheusEval`.\n\n😱 Using `PrometheusEval` running their 7B variant with vLLM in a single L40 on top of https://huggingface.co/datasets/HuggingFaceH4/instruction-dataset, we got the 327 existing prompt-completion pairs evaluated and pushed to the Hub in less than 2 minutes!\n\nFind the generated dataset and the code at https://huggingface.co/datasets/distilabel-internal-testing/instruction-dataset-prometheus","author":{"_id":"60f0608166e5701b80ed3f02","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/60f0608166e5701b80ed3f02/BHso-wSWpR9b8b8CKvodC.jpeg","fullname":"Alvaro 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