📢 The second part of the tutorial series on tiny integration LLMs integration in web with streaming and batching support.
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📢 The second part of the tutorial series on tiny integration LLMs integration in web with streaming and batching support.
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🎬️ 
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🎬️ 
https://youtu.be/yNKYJzlKxh0
https://youtu.be/yNKYJzlKxh0
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With the second part we making step from sending data chunks  ➡️ integration of LLM through the third-party providers This would be helpful to understand the minimalistic concept that is supposed to be done in order to support the streaming of large language models.
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With the second part we making step from sending data chunks  ➡️ integration of LLM through the third-party providers This would be helpful to understand the minimalistic concept that is supposed to be done in order to support the streaming of large language models.
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🌟 Powered by:
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🌟 Powered by:
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🧑‍💻 bulk-chain (inference framework): 
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🧑‍💻 bulk-chain (inference framework): 
https://github.com/nicolay-r/bulk-chain
https://github.com/nicolay-r/bulk-chain
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↗️ nlp-thirdgate (providers): 
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↗️ nlp-thirdgate (providers): 
https://github.com/nicolay-r/nlp-thirdgate
https://github.com/nicolay-r/nlp-thirdgate
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📢 The second part of the tutorial series on tiny integration LLMs integration in web with streaming and batching support.

🎬️ https://youtu.be/yNKYJzlKxh0

With the second part we making step from sending data chunks  ➡️ integration of LLM through the third-party providers This would be helpful to understand the minimalistic concept that is supposed to be done in order to support the streaming of large language models.

🌟 Powered by:
🧑‍💻 bulk-chain (inference framework): https://github.com/nicolay-r/bulk-chain
↗️ nlp-thirdgate (providers): https://github.com/nicolay-r/nlp-thirdgate
👍
John6666