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 www.4async.com
???? Hypothetical Document Embeddings (HyDE) - 2
| | www.anyscale.com
Turbocharge LangChain: Guide to 20x Faster Embedding
3.2 parsecs away

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| | In part 2 of this blog series, we show you how to turbocharge embeddings in LLM workflows using LangChain and Ray Data.
| | www.antstack.com
OpenAI + DynamoDB Part 2: Using Partition and Sort Key for Chat Memory with LangChain | AntStack - Full-Stack Serverless Company
3.6 parsecs away

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| | Learn how to enhance your LangChain chatbot with AWS DynamoDB using partition and sort keys for efficient chat memory management. Follow this detailed tutorial now!
| | mobiarch.wordpress.com
Run RAG Locally Using Mistral, Ollama and Langchain | mobiarch
1.5 parsecs away

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| | Ollama makes it super easy to run open source LLMs locally. You can expect decent performance even in small laptops. Ollama is an alternative to Hugging Face for running models locally. Hugging Face libraries run on top of Tensorflow or Torch. Ollama uses llama.cpp as the underlying runtime. This makes Ollama very easy to get...
| | shyamal.me
Reinforcement fine-tuning and reward engineering | shyamal's space
40.4 parsecs away

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| RFT is still in its early days, but it's a powerful tool - making it surprisingly easy to create expert models for specific domains with less training data.