betterdataai
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PII_DETECTION_MODEL

Text Generation

text-generation-inference

Model card Files Files and versions

srini98 commited on Aug 7, 2024

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 library_name: transformers
-tags: []
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 # Model Card
@@ -27,7 +27,7 @@ The model is built on top of the decoder transformer model (Qwen2-0.5B). We used
 With the advent of chatGPT , professionals and organizations use public chat interfaces for various applications. This often leads to leakage of PII data which causes privacy issues as users enter names , dates or even API keys etc to give the model better context. With the PII class tags, these confidential information can be masked out as class tags which enable the end models to understand context without data leaving the server. Even developers or teams building applications with the help of third party API's can use these models for better privacy. The image below illustrates this:
-![image/png](https://huggingface.co/betterdataai/PII_DETECTION_MODEL/blob/main/pii_image.png")
 The PII model shouldn't add too much latency and be able to take in long documents, therefore we used the Qwen 0.5B as the base model. Another consideration for the model size was that we felt a model for privacy should be easy to run even on CPUs. We do have larger models in house with better performance. We have coverage for south east asian langauges as well as giving the user the ability to define custom user classes as part of our plans.

 ---
 library_name: transformers
+pipeline_tag: text-generation
 ---
 # Model Card
 With the advent of chatGPT , professionals and organizations use public chat interfaces for various applications. This often leads to leakage of PII data which causes privacy issues as users enter names , dates or even API keys etc to give the model better context. With the PII class tags, these confidential information can be masked out as class tags which enable the end models to understand context without data leaving the server. Even developers or teams building applications with the help of third party API's can use these models for better privacy. The image below illustrates this:
+![image/png](https://huggingface.co/betterdataai/PII_DETECTION_MODEL/blob/main/pii_image.png)
 The PII model shouldn't add too much latency and be able to take in long documents, therefore we used the Qwen 0.5B as the base model. Another consideration for the model size was that we felt a model for privacy should be easy to run even on CPUs. We do have larger models in house with better performance. We have coverage for south east asian langauges as well as giving the user the ability to define custom user classes as part of our plans.