Instructions to use usman-yello/job-tagging-summary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use usman-yello/job-tagging-summary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="usman-yello/job-tagging-summary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("usman-yello/job-tagging-summary") model = AutoModelForSequenceClassification.from_pretrained("usman-yello/job-tagging-summary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Card for Model ID
This model is a multilabel classifier that takes an input string containing position_title and summary of responsibilities, and returns job tags.
Model Details
Fine tuned bert-base-uncased for custom job tagging.
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by: [Usman Naveed]
- Model type: [Encoder|Text Classifier]
- Language(s) (NLP): [English]
- Finetuned from model [optional]: [bert-base-uncased]
Model Sources [optional]
Uses
This model is only intended to classify jobs into job tags.
Bias, Risks, and Limitations
The dataset trained on was imbalanced, and contained more Engineering and Finance jobs than any other tag. This may cause bias towards Engineering and Finance tags.
[More Information Needed]
How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
Training Details
Training Data
Dataset used to train this model: https://huggingface.co/datasets/usman-yello/job-tagging-with-summary
Preprocessing [optional]
- Remove HTML and markdown from the responsibilties
- Create a new text column which is the concatenation of the position_title and the responsibilities, use this column
Testing Data, Factors & Metrics
Testing Data
[More Information Needed]
Factors
[More Information Needed]
Metrics
[More Information Needed]
Results
[More Information Needed]
Summary
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