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Merge pull request #945 from rpgoldman/rpgoldman-readme-patch-1
Enhance README "Some other examples" section
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README.md

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@@ -146,10 +146,11 @@ You can find other examples tweeted by [@lateinteraction](https://twitter.com/la
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- [Generating Tweets for QA, by Arnav Singhvi](https://colab.research.google.com/github/stanfordnlp/dspy/blob/main/examples/tweets/tweets_assertions.ipynb)
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- [Compiling LCEL runnables from LangChain in DSPy](https://github.com/stanfordnlp/dspy/blob/main/examples/tweets/compiling_langchain.ipynb)
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- [AI feedback, or writing LM-based metrics in DSPy](https://github.com/stanfordnlp/dspy/blob/main/examples/tweets/tweet_metric.py)
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- [DSPy Optimizers Benchmark on a bunch of different tasks, by Michael Ryan](https://github.com/stanfordnlp/dspy/tree/main/testing/README.md)
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- [Indian Languages NLI with gains due to compiling by Saiful Haq](https://github.com/saifulhaq95/DSPy-Indic/blob/main/indicxlni.ipynb)
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- [DSPy on BIG-Bench Hard Example, by Chris Levy](https://drchrislevy.github.io/posts/dspy/dspy.html)
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- [Using Ollama with DSPy for Mistral (quantized) by @jrknox1977](https://gist.github.com/jrknox1977/78c17e492b5a75ee5bbaf9673aee4641)
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- [Using DSPy, "The Unreasonable Effectiveness of Eccentric Automatic Prompts" (paper) by VMware's Rick Battle & Teja Gollapudi, and interview at TheRegister](https://www.theregister.com/2024/02/22/prompt_engineering_ai_models/)
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- [Using DSPy, "The Unreasonable Effectiveness of Eccentric Automatic Prompts" (paper) by VMware's Rick Battle & Teja Gollapudi](https://arxiv.org/abs/2402.10949), and [interview at TheRegister](https://www.theregister.com/2024/02/22/prompt_engineering_ai_models/)
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- [Optimizing Performance of Open Source LM for Text-to-SQL using DSPy and vLLM, by Juan Ovalle](https://github.com/jjovalle99/DSPy-Text2SQL)
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- Typed DSPy (contributed by [@normal-computing](https://github.com/normal-computing))
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- [Using DSPy to train Gpt 3.5 on HumanEval by Thomas Ahle](https://github.com/stanfordnlp/dspy/blob/main/examples/functional/functional.ipynb)

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