- h
pii-masking-43k
- huggingface.co
Updated Jul 1, 2023
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EmailClick to copy linkLink copiedCiteAi4Privacy (2023). pii-masking-43k [Dataset]. http://doi.org/10.57967/hf/0824CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.Unique identifierhttps://doi.org/10.57967/hf/0824Dataset updatedJul 1, 2023Dataset authored and provided byAi4PrivacyDescriptionPurpose and Features
The purpose of the model and dataset is to remove personally identifiable information (PII) from text, especially in the context of AI assistants and LLMs. The model is a fine-tuned version of "Distilled BERT", a smaller and faster version of BERT. It was adapted for the task of token classification based on the largest to our knowledge open-source PII masking dataset, which we are releasing simultaneously. The model size is 62 million parameters. The… See the full description on the dataset page: https://huggingface.co/datasets/ai4privacy/pii-masking-43k.
- h
pii-masking-65k
- huggingface.co
Updated Apr 5, 2024ShareFacebookTwitterEmailClick to copy linkLink copiedCiteAi4Privacy (2024). pii-masking-65k [Dataset]. http://doi.org/10.57967/hf/2012CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.Unique identifierhttps://doi.org/10.57967/hf/2012Dataset updatedApr 5, 2024Dataset authored and provided byAi4PrivacyDescriptionPurpose and Features
The purpose of the model and dataset is to remove personally identifiable information (PII) from text, especially in the context of AI assistants and LLMs. The model is a fine-tuned version of "Distilled BERT", a smaller and faster version of BERT. It was adapted for the task of token classification based on the largest to our knowledge open-source PII masking dataset, which we are releasing simultaneously. The model size is 62 million parameters. The… See the full description on the dataset page: https://huggingface.co/datasets/ai4privacy/pii-masking-65k.
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FacebookTwitterEmailPurpose and Features
The purpose of the model and dataset is to remove personally identifiable information (PII) from text, especially in the context of AI assistants and LLMs. The model is a fine-tuned version of "Distilled BERT", a smaller and faster version of BERT. It was adapted for the task of token classification based on the largest to our knowledge open-source PII masking dataset, which we are releasing simultaneously. The model size is 62 million parameters. The… See the full description on the dataset page: https://huggingface.co/datasets/ai4privacy/pii-masking-43k.