#textembedding — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #textembedding, aggregated by home.social.
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🚀😆 Ternlight: the pinnacle of bloat! Because who doesn’t want to sacrifice precious #browser resources for an "efficient" 7 MB model? 📦✨ The future is here: embedding text at lightning speed, and praying your CPU doesn’t catch fire. 🔥🖥️
https://ternlight-demo.vercel.app/ #Ternlight #Bloat #Efficiency #TextEmbedding #CPUOverload #FutureTech #HackerNews #ngated -
🚀😆 Ternlight: the pinnacle of bloat! Because who doesn’t want to sacrifice precious #browser resources for an "efficient" 7 MB model? 📦✨ The future is here: embedding text at lightning speed, and praying your CPU doesn’t catch fire. 🔥🖥️
https://ternlight-demo.vercel.app/ #Ternlight #Bloat #Efficiency #TextEmbedding #CPUOverload #FutureTech #HackerNews #ngated -
🚀😆 Ternlight: the pinnacle of bloat! Because who doesn’t want to sacrifice precious #browser resources for an "efficient" 7 MB model? 📦✨ The future is here: embedding text at lightning speed, and praying your CPU doesn’t catch fire. 🔥🖥️
https://ternlight-demo.vercel.app/ #Ternlight #Bloat #Efficiency #TextEmbedding #CPUOverload #FutureTech #HackerNews #ngated -
🚀😆 Ternlight: the pinnacle of bloat! Because who doesn’t want to sacrifice precious #browser resources for an "efficient" 7 MB model? 📦✨ The future is here: embedding text at lightning speed, and praying your CPU doesn’t catch fire. 🔥🖥️
https://ternlight-demo.vercel.app/ #Ternlight #Bloat #Efficiency #TextEmbedding #CPUOverload #FutureTech #HackerNews #ngated -
🚀😆 Ternlight: the pinnacle of bloat! Because who doesn’t want to sacrifice precious #browser resources for an "efficient" 7 MB model? 📦✨ The future is here: embedding text at lightning speed, and praying your CPU doesn’t catch fire. 🔥🖥️
https://ternlight-demo.vercel.app/ #Ternlight #Bloat #Efficiency #TextEmbedding #CPUOverload #FutureTech #HackerNews #ngated -
Compatible with existing embed_content endpoint via #GoogleAIStudio 📊 Outperforms previous #textembedding models across diverse tasks including retrieval and classification
https://developers.googleblog.com/en/gemini-embedding-available-gemini-api/
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Compatible with existing embed_content endpoint via #GoogleAIStudio 📊 Outperforms previous #textembedding models across diverse tasks including retrieval and classification
https://developers.googleblog.com/en/gemini-embedding-available-gemini-api/
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Compatible with existing embed_content endpoint via #GoogleAIStudio 📊 Outperforms previous #textembedding models across diverse tasks including retrieval and classification
https://developers.googleblog.com/en/gemini-embedding-available-gemini-api/
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Compatible with existing embed_content endpoint via #GoogleAIStudio 📊 Outperforms previous #textembedding models across diverse tasks including retrieval and classification
https://developers.googleblog.com/en/gemini-embedding-available-gemini-api/
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Compatible with existing embed_content endpoint via #GoogleAIStudio 📊 Outperforms previous #textembedding models across diverse tasks including retrieval and classification
https://developers.googleblog.com/en/gemini-embedding-available-gemini-api/
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Personalized arXiv Recommendation Service
https://fed.brid.gy/r/https://blog.haoxiang.org/2024/02/personalized-arxiv-recommendation-service/