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📢 If you're aimed at processing complex dependencies in spreadsheet data with LLM Chain-of-Thought technique, then this update might be valuable for you 💎
📢 If you're aimed at processing complex dependencies in spreadsheet data with LLM Chain-of-Thought technique, then this update might be valuable for you 💎
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The updated 📦 bulk-chain-0.24.1 which is aimed at iterative processing of CSV/JSONL data with no-string dependencies from third party LLM frameworks is out 🎉
The updated 📦 bulk-chain-0.24.1 which is aimed at iterative processing of CSV/JSONL data with no-string dependencies from third party LLM frameworks is out 🎉
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📦: 
📦: 
link
https://pypi.org/project/bulk-chain/0.24.1/
https://pypi.org/project/bulk-chain/0.24.1/
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🌟: 
🌟: 
link
https://github.com/nicolay-r/bulk-chain
https://github.com/nicolay-r/bulk-chain
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📘: 
📘: 
link
https://github.com/nicolay-r/bulk-chain/issues/26
https://github.com/nicolay-r/bulk-chain/issues/26
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The key feature of bulk-chain is SQLite caching that saves your time ⏰️ and money 💵 by guarantee no-data-lost, which is important once using the remote LLM providers such as OpenAI, ReplicateIO, OpenRouter, etc.
The key feature of bulk-chain is SQLite caching that saves your time ⏰️ and money 💵 by guarantee no-data-lost, which is important once using the remote LLM providers such as OpenAI, ReplicateIO, OpenRouter, etc.
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🔧 This release has the following updates:
🔧 This release has the following updates:
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✅ Improved stability for various header conditions and the related support from SQLite
✅ Improved stability for various header conditions and the related support from SQLite
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✅ Manual setup for ID column / assigning the ID
✅ Manual setup for ID column / assigning the ID
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✅ Make CSV-related setups dynamic, that refers to the related Python 📦 csv package.
✅ Make CSV-related setups dynamic, that refers to the related Python 📦 csv package.
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Quick start on GoogleColab:
Quick start on GoogleColab:
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📙: 
📙: 
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https://colab.research.google.com/github/nicolay-r/bulk-chain/blob/master/bulk_chain_tutorial.ipynb
https://colab.research.google.com/github/nicolay-r/bulk-chain/blob/master/bulk_chain_tutorial.ipynb
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Below is an example of the three simple steps in pictures:
Below is an example of the three simple steps in pictures:
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1. ⬇️ Package installation 
1. ⬇️ Package installation 
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2. ✍️ Declaring schema
2. ✍️ Declaring schema
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3. 🚀 Launching inference for your data with Replicate and 🤖 
3. 🚀 Launching inference for your data with Replicate and 🤖 
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https://huggingface.co/meta-llama/Llama-3.1-405B
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meta-llama/Llama-3.1-405B
https://huggingface.co/meta-llama/Llama-3.1-405B
📢 If you're aimed at processing complex dependencies in spreadsheet data with LLM Chain-of-Thought technique, then this update might be valuable for you 💎

The updated 📦 bulk-chain-0.24.1 which is aimed at iterative processing of CSV/JSONL data with no-string dependencies from third party LLM frameworks is out 🎉

📦: https://pypi.org/project/bulk-chain/0.24.1/
🌟: https://github.com/nicolay-r/bulk-chain
📘: https://github.com/nicolay-r/bulk-chain/issues/26

The key feature of bulk-chain is SQLite caching that saves your time ⏰️ and money 💵 by guarantee no-data-lost, which is important once using the remote LLM providers such as OpenAI, ReplicateIO, OpenRouter, etc.

🔧 This release has the following updates:
✅ Improved stability for various header conditions and the related support from SQLite
✅ Manual setup for ID column / assigning the ID
✅ Make CSV-related setups dynamic, that refers to the related Python 📦 csv package.

Quick start on GoogleColab:
📙: https://colab.research.google.com/github/nicolay-r/bulk-chain/blob/master/bulk_chain_tutorial.ipynb

Below is an example of the three simple steps in pictures:
1. ⬇️ Package installation 
2. ✍️ Declaring schema
3. 🚀 Launching inference for your data with Replicate and 🤖 https://huggingface.co/meta-llama/Llama-3.1-405B
👀
John6666 Sri-Vigneshwar-DJ EquinoxElahin
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prithivMLmods kaykyramos