Instructions to use Apizhai/Albert-IT-JobRecommendation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Apizhai/Albert-IT-JobRecommendation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Apizhai/Albert-IT-JobRecommendation")# Load model directly from transformers import AutoTokenizer, AlbertForMultiLabelSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Apizhai/Albert-IT-JobRecommendation") model = AlbertForMultiLabelSequenceClassification.from_pretrained("Apizhai/Albert-IT-JobRecommendation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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pipeline_tag: text-classification
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NairiSoft is looking for a highly qualified person with deep knowledge and
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Armeconombank OJSC is looking for a .Net Developer to join its team. The
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Software Developer will take part in design and development projects.
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example_title: Current Position Requirments 3
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pipeline_tag: text-classification
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widget:
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NairiSoft is looking for a highly qualified person with deep knowledge and
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Armeconombank OJSC is looking for a .Net Developer to join its team. The
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Software Developer will take part in design and development projects.
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example_title: Current Position Requirments 3
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language:
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- en
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tags:
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- albert
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- text-classification
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- recommendation
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- job
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- albert-base-v2
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- IT
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