Instructions to use mujtabakk/DistilBert-LinkedIn-Posts-Classfication with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mujtabakk/DistilBert-LinkedIn-Posts-Classfication with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mujtabakk/DistilBert-LinkedIn-Posts-Classfication")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mujtabakk/DistilBert-LinkedIn-Posts-Classfication") model = AutoModelForSequenceClassification.from_pretrained("mujtabakk/DistilBert-LinkedIn-Posts-Classfication", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a6e8c1c022e52deb8c405cae153ae813a3787aa2a91368b3c279b09345bab3f
- Size of remote file:
- 268 MB
- SHA256:
- 48f25e0c458fb769833da81ca3c2c3e09f7738113505822c5b2af053351632ca
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