We evaluated Code Llama against existing solutions on both HumanEval & MBPP.
– It performed better than open-source, code-specific LLMs & Llama 2.
– Code Llama 34B scored the highest vs other SOTA open solutions on MBPP — on par w/ ChatGPT. More info https://
bit.ly/45JiPwJ
@aiatmeta
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Code Llama Outperforms Open-Source Solutions on HumanEval MBPP
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Code Llama Now Available in Hugging Face Playground
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You can try Code Llama now in the Code Llama playground @huggingface space — it's also available in the Hugging Face ecosystem, starting with transformers version 4.33.
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Meta Releases Code Llama, Advanced Open-Source Coding Model
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Today we’re releasing Code Llama, a large language model built on top of Llama 2, fine-tuned for coding & state-of-the-art for publicly available coding tools.
— AI at Meta (@AIatMeta) 24 août 2023
Keeping with our open approach, Code Llama is publicly-available now for both research & commercial use.
More ⬇️Today we’re releasing Code Llama, a large language model built on top of Llama 2, fine-tuned for coding & state-of-the-art for publicly available coding tools. Keeping with our open approach, Code Llama is publicly-available now for both research & commercial use. More
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Llama 2 Apps and Experiences on MediaTek Devices
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We're excited to see all the new apps and experiences enabled by Llama 2 on MediaTek-powered devices!
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Try Other Tasks on Hugging Face Space
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You can try other tasks on our @huggingface space https://
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SeamlessM4T Breakthrough in Multilingual Speech Translation
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SeamlessM4T represents a significant breakthrough in the field of speech-to-speech & speech-to-text by addressing the challenges of limited language coverage & a reliance on separate systems. More details https://
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SeamlessM4T: Single System Approach for Superior Translation Quality
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Compared to cascaded approaches, SeamlessM4T's single system approach reduces errors & delays, increasing translation efficiency & quality, delivering state-of-the-art results. Want to see it for yourself, try the demo https://
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Meta Releases SeamlessM4T Translation Model Openly
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We believe SeamlessM4T represents a significant breakthrough and as part of our open approach, today we're publicly releasing this work under a CC BY-NC 4.0 license so that others can continue to build on this important field of study. Get the code https://
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SeamlessM4T: All-in-One Multilingual Multimodal Translation Model
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Introducing SeamlessM4T, the first all-in-one, multilingual multimodal translation model. This single model can perform tasks across speech-to-text, speech-to-speech, text-to-text translation & speech recognition for up to 100 languages depending on the task. Details
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Wake Word Detection: Alignment-Based, Alignment-Free & Hybrid Approaches
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Handling the Alignment for Wake Word Detection: A Comparison Between Alignment-Based, Alignment-Free & Hybrid Approaches https://
bit.ly/3YFqgmc This paper focuses on understanding alignment's role in developing a wake-word system that answers a generic phrase.