Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
resume-parsing
nlp
text-embeddings-inference
Instructions to use amosify/resume-section-classifier-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amosify/resume-section-classifier-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amosify/resume-section-classifier-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amosify/resume-section-classifier-v1") model = AutoModelForSequenceClassification.from_pretrained("amosify/resume-section-classifier-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 838aaef4b8239bb1944a8c8005548af9731a64e79b6bdcd199f6d491f7086356
- Size of remote file:
- 5.27 kB
- SHA256:
- 719d7d8ba152b7a2ad95ac2af545f8cd8b2521bf1791e81e3bddf3db403e83b7
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