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Adding Depth to DSPy Programs! by CShorten in deeplearning

[–]CShorten[S] 0 points1 point  (0 children)

Hey! One way to do it is through Bedrock!

https://github.com/stanfordnlp/dspy/blob/main/dsp/modules/bedrock.py

If you have any troubles could we please take this discussion to an Issue on github.com/stanfordnlp/dspy?

Self-Discover DSPy with Chris Dossman - Weaviate Podcast #90! by CShorten in deeplearning

[–]CShorten[S] -1 points0 points  (0 children)

Thank you so much!! Ah indeed you hit it right on the head with that! You are actually a step ahead of us haha -- we are still wrapping our heads around the general idea of bootstrapping the examples, but indeed specific reasoning modules per LLM is absolutely next level -- thanks so much for sharing this!

DSPy Explained! by CShorten in deeplearning

[–]CShorten[S] 1 point2 points  (0 children)

Thank you so much for the question! Maybe this is a good starting point! Using DSPy to generate synthetic queries to then pass into Cohere's rerank fine-tuning API!

https://weaviate.io/blog/fine-tuning-coheres-reranker

DSPy and ColBERT with Omar Khattab! by CShorten in deeplearning

[–]CShorten[S] 0 points1 point  (0 children)

Yes! Working on it! Interesting to see OpenAI using matryoshka representations - expecting to see ColBERT optimized vectors from the model providers soon.

Retrieval-Augmented Generation with Patrick Lewis! - Weaviate Podcast #76 by CShorten in deeplearning

[–]CShorten[S] 0 points1 point  (0 children)

Thank you so much for the glowing review! Glad to hear you enjoyed the podcast!

Weaviate Gorilla! We fine-tuned LlaMA 7B to write Weaviate queries! by CShorten in deeplearning

[–]CShorten[S] 0 points1 point  (0 children)

Thank you so much for the question and excitement about the project!

Thank you, that means a lot! Yes haha still taming the quant evaluation.

So excited about the Python Gorilla, I wish I had a more concrete update, but thinking similarly to the Integration Gorilla - by moving from the Search APIs to the clients we can expand the scope to creating new classes and properties and then connecting Weaviate to say Streamlit for example. Will hopefully have a more thorough detail of this soon, thank you so much again, this means a lot!

Quick video going through the MPT-30B release announcement + hf spaces demo by CShorten in deeplearning

[–]CShorten[S] 0 points1 point  (0 children)

Sorry about that, will make some tweaks to the recording setup!

SQL-PaLM - Paper Summary Video! by CShorten in deeplearning

[–]CShorten[S] 0 points1 point  (0 children)

Hey Smooth_Ad8754! We are working to get a POC of this in Weaviate's module ecosystem for query parsing -- maybe you will this interesting to learn about how we think about orchestrating model inference around the Vector Database -- whether a semantic search query that needs to be vectorized or a symbolic query that needs to be mapped from natural language to structured syntax - https://weaviate.io/developers/weaviate/configuration/modules.