SentenceTransformer based on sentence transformers/all mpnet base v2 This is a sentence transformers model specifically trained for job title matching and similarity. It's finetuned from sentence transformers/all mpnet base v2 on a large dataset of job titles and their associated skills/requirements. The model maps job titles and descriptions to a 1024 dimensional dense vector space and can be used for semantic job title matching, job similarity search, and related HR/recruitment tasks. Model Details Model Description Model Type: Sentence Transformer Base model: sentence transformers/all mpnet base v2 Maximum Sequence Length: 64 tokens Output Dimensionality: 1024 tokens Similarity Function: Cosine Similarity Training Dataset: 5.5M+ job title skills pairs Primary Use Case: Job title matching and similarity Performance: Achieves 0.6457 MAP on TalentCLEF benchmark Model Sources Documentation: Sentence Transformers Documentation Repository: Sentence Transformers on GitHub Hugging Face: Sentence Transformers on Hugging Face Full Model Architecture Usage Direct Usage (Sentence Transformers) First install the required packages: Then you can load and use the model with the following code:…
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