vicgalle

--- language: multilingual license: mit tags: - zero-shot-classification - nli - pytorch datasets: - mnli - xnli - facebook/anli pipeline_tag: zero-shot-classification widget: - text: De pugna erat fantastic. Nam Crixo decem quam dilexit et praeciderunt caput aemulus. candidate_labels: violent, peaceful - text: La película empezaba bien pero terminó siendo un desastre. candidate_labels: positivo, negativo, neutral - text: La película empezó siendo un desastre pero en general fue bien. candidate_

This is a merge of pre-trained language models created using mergekit. This model was merged using the linear merge method. The following models were included in the merge: vicgalle/Configurable-Mistral-7B kaist-ai/janus-dpo-7b The following YAML configuration was used to produce this model:

This model has been trained by fine-tuning gliner-community/glinersmall-v2.5 on the urchade/synthetic-pii-ner-mistral-v1 dataset. This model is capable of recognizing various types of personally identifiable information (PII), including but not limited to these entity types: person, organization, phone number, address, passport number, email, credit card number, social security number, health insurance id number, date of birth, mobile phone number, bank account number, medication, cpf, driver's license number, tax identification number, medical condition, identity card number, national id number, ip address, email address, iban, credit card expiration date, username, health insurance number, registration number, student id number, insurance number, flight number, landline phone number, blood type, cvv, reservation number, digital signature, social media handle, license plate number, cnpj, postal code, passportnumber, serial number, vehicle registration number, credit card brand, fax number, visa number, insurance company, identity document number, transaction number, national health insurance number, cvc, birth certificate number, train ticket number, passport expiration date, and socialsecuritynumber. Note: it may be beneficial to lower the threshold (see the previous example), to extract all related entities.

Merge-Mistral-Prometheus-7B is a merge of the following models using LazyMergekit: prometheus-eval/prometheus-7b-v2.0 4bit/Mistral-7B-Instruct-v0.1