Python/AI Engineer at Wokegenics Solutions Private Limited
Real User
Top 20
2024-09-04T14:56:10Z
Sep 4, 2024
We use the tool to extract data from a PDF file, give the text data to any Hugging Face model like Meta or Llama, and get the results from those models according to the prompt. It's basically like having a chat with the PDF file.
I use Hugging Face to fine-tune large language models. We take our client's use case and an open-source model already deployed, download the model artifacts, and fine-tune the models according to our specific use case.
I use Hugging Face primarily to work with open LLM models. I recently started using the open LOM models and also use embedding models. I use these models to train custom data and monitor our desktop custom models after training and deployment.
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This is a simple personal project, non-commercial. As a student, that's all I do.
We use the tool to extract data from a PDF file, give the text data to any Hugging Face model like Meta or Llama, and get the results from those models according to the prompt. It's basically like having a chat with the PDF file.
I use Hugging Face to fine-tune large language models. We take our client's use case and an open-source model already deployed, download the model artifacts, and fine-tune the models according to our specific use case.
I use Hugging Face primarily to work with open LLM models. I recently started using the open LOM models and also use embedding models. I use these models to train custom data and monitor our desktop custom models after training and deployment.
Hugging Face is an open-source desktop solution.
I mainly use it for machine learning and AI. It's for a large language model, like LLaMA.