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Episode 175 : Evaluateur de LLM

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Content provided by Vincent Heuschling, Alexander Dejanovski, Jérôme Mainaud, and Nicolas Steinmetz. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Vincent Heuschling, Alexander Dejanovski, Jérôme Mainaud, and Nicolas Steinmetz or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
* Why can't datacenter operators stop thinking about atomic power? -> https://www.theregister.com/2023/09/27/datacenters_nuclear_power
### LLM fever* Evaluate LLMs and RAG a practical example using Langchain and Hugging Face -> https://www.philschmid.de/evaluate-llm
* Introducing the Giskard Bot: Enhancing LLM Testing & Debugging on Hugging Face -> https://huggingface.co/blog/JMJM/giskard-llm-testing-and-debugging-hf
* Introducing Canopy: An easy, free, and flexible RAG framework powered by Pinecone -> https://www.pinecone.io/blog/canopy-rag-framework/
### Tools* Pijul -> https://pijul.org/
* Pijul la théorie -> https://pijul.org/manual/theory.html
### meetup* "Ou va la modern Data Stack ?" le 31 janvier 2024 chez Criteo -> https://www.linkedin.com/company/modern-data-stack-france/
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Cette publication est sponsorisée par Affini-Tech et CerenIT.
CerenIT vous accompagne pour concevoir, industrialiser ou automatiser vos plateformes mais aussi pour faire parler vos données temporelles. Ecrivez nous à contact@cerenit.fr et retrouvez-nous aussi au Time Series France.
Affini-Tech vous accompagne dans tous vos projets Cloud et Data, pour Imaginer, Expérimenter et Executer vos services ! (Affini-Tech, Datatask) Consulter le blog d’Affini-Tech et le blog de Datatask pour en savoir plus. On recrute ! Venez cruncher de la data avec nous ! Ecrivez nous à recrutement@affini-tech.com
Le générique a été composé et réalisé par Maxence Lecointe
  continue reading

230 episoade

Artwork

Episode 175 : Evaluateur de LLM

Big Data Hebdo

69 subscribers

published

iconDistribuie
 
Manage episode 384773466 series 1456667
Content provided by Vincent Heuschling, Alexander Dejanovski, Jérôme Mainaud, and Nicolas Steinmetz. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Vincent Heuschling, Alexander Dejanovski, Jérôme Mainaud, and Nicolas Steinmetz or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
* Why can't datacenter operators stop thinking about atomic power? -> https://www.theregister.com/2023/09/27/datacenters_nuclear_power
### LLM fever* Evaluate LLMs and RAG a practical example using Langchain and Hugging Face -> https://www.philschmid.de/evaluate-llm
* Introducing the Giskard Bot: Enhancing LLM Testing & Debugging on Hugging Face -> https://huggingface.co/blog/JMJM/giskard-llm-testing-and-debugging-hf
* Introducing Canopy: An easy, free, and flexible RAG framework powered by Pinecone -> https://www.pinecone.io/blog/canopy-rag-framework/
### Tools* Pijul -> https://pijul.org/
* Pijul la théorie -> https://pijul.org/manual/theory.html
### meetup* "Ou va la modern Data Stack ?" le 31 janvier 2024 chez Criteo -> https://www.linkedin.com/company/modern-data-stack-france/
------------------
Cette publication est sponsorisée par Affini-Tech et CerenIT.
CerenIT vous accompagne pour concevoir, industrialiser ou automatiser vos plateformes mais aussi pour faire parler vos données temporelles. Ecrivez nous à contact@cerenit.fr et retrouvez-nous aussi au Time Series France.
Affini-Tech vous accompagne dans tous vos projets Cloud et Data, pour Imaginer, Expérimenter et Executer vos services ! (Affini-Tech, Datatask) Consulter le blog d’Affini-Tech et le blog de Datatask pour en savoir plus. On recrute ! Venez cruncher de la data avec nous ! Ecrivez nous à recrutement@affini-tech.com
Le générique a été composé et réalisé par Maxence Lecointe
  continue reading

230 episoade

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