📢 For those who wish to apply DeepSeek-R1 for handling tabular / streaming data using schema of prompts (CoT), the OpenRouter AI hosts API for accessing:
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📢 For those who wish to apply DeepSeek-R1 for handling tabular / streaming data using schema of prompts (CoT), the OpenRouter AI hosts API for accessing:
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https://openrouter.ai/deepseek/deepseek-r1
https://openrouter.ai/deepseek/deepseek-r1
link
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The no-string option to quick start with using DeepSeek-R1 includes three steps:
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The no-string option to quick start with using DeepSeek-R1 includes three steps:
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✅ OpenRouter provider: 
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✅ OpenRouter provider: 
https://github.com/nicolay-r/nlp-thirdgate/blob/master/llm/open_router.py
https://github.com/nicolay-r/nlp-thirdgate/blob/master/llm/open_router.py
link
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✅ Bulk-chain for infering data: 
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✅ Bulk-chain for infering data: 
https://github.com/nicolay-r/bulk-chain
https://github.com/nicolay-r/bulk-chain
link
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✅  Json Schema for Chain-of-Though reasoning (see screenshot 📷 below)
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✅  Json Schema for Chain-of-Though reasoning (see screenshot 📷 below)
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📺 below is a screenshot of how to quick start the demo, in which you can test your schema for LLM responses. It would ask to type all the parameters first for completing the requests (which is 
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📺 below is a screenshot of how to quick start the demo, in which you can test your schema for LLM responses. It would ask to type all the parameters first for completing the requests (which is 
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`text`
inline_code
 within this example).
text
 within this example).
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📃 To apply it for JSONL/CSV data, you can use 
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📃 To apply it for JSONL/CSV data, you can use 
--src
`--src`
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 shell parameter for passing the related file
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 shell parameter for passing the related file
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⏳ As for time, OpenRouter finds me relatively slow with 30~40 seconds per request
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⏳ As for time, OpenRouter finds me relatively slow with 30~40 seconds per request
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Models:
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Models:
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https://huggingface.co/deepseek-ai/DeepSeek-R1
deepseek-ai/DeepSeek-R1
model
resource
https://huggingface.co/deepseek-ai/DeepSeek-R1
📢 For those who wish to apply DeepSeek-R1 for handling tabular / streaming data using schema of prompts (CoT), the OpenRouter AI hosts API for accessing:
https://openrouter.ai/deepseek/deepseek-r1

The no-string option to quick start with using DeepSeek-R1 includes three steps:
✅ OpenRouter provider: https://github.com/nicolay-r/nlp-thirdgate/blob/master/llm/open_router.py
✅ Bulk-chain for infering data: https://github.com/nicolay-r/bulk-chain
✅  Json Schema for Chain-of-Though reasoning (see screenshot 📷 below)

📺 below is a screenshot of how to quick start the demo, in which you can test your schema for LLM responses. It would ask to type all the parameters first for completing the requests (which is `text` within this example).

📃 To apply it for JSONL/CSV data, you can use `--src` shell parameter for passing the related file

⏳ As for time, OpenRouter finds me relatively slow with 30~40 seconds per request

Models:
https://huggingface.co/deepseek-ai/DeepSeek-R1
👀
John6666 Xdotnet Nielly
🔥
prithivMLmods
👍
nitish25
6735bb352a3c30eac4dc7207
/avatars/e4671bba33727bc114bfcfafbf72d187.svg
Vishwajeet Ranjan
vkrnitd
user