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Excited to introduce DeepSeek R1 fine-tuning with Firecrawl 🔥 Learn how to fine-tune DeepSeek's R1 model on custom instruction datasets generated by Firecrawl's web data extraction. Train your own AI expert to answer domain-specific questions about your website!
40,189 görüntüleme • 1 yıl önce •via X (Twitter)
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See the open-source code, read the explainer article and get your Firecrawl API key here:

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@deepseek_ai @firecrawl_dev This is great work!

@deepseek_ai @firecrawl_dev Very cool!

@firecrawl_dev @deepseek_ai I’m having an issue with the extract api… left you a message

@deepseek_ai @firecrawl_dev Any plans to enhance the web scraping APIs in firecrawl? I’d like the API to return less irrelevant elements and cleaner markdown, even if a bit slower/more-expensive.

@deepseek_ai @firecrawl_dev This is awesome, will check to add it to to make better synthetic data

@deepseek_ai @firecrawl_dev Really cool! I really need to take some time to check out Firecrawl 🔥

@deepseek_ai @firecrawl_dev Firecrawl is a very powerful tool ✊

@deepseek_ai @firecrawl_dev can you compare the pros and cons of having the model fine-tuned with the Firecrawl Doc and using the model as it is in a RAG solution with the same documentation?

