Instructions to use philmunz/poc_finetuned_ud with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philmunz/poc_finetuned_ud with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="philmunz/poc_finetuned_ud")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("philmunz/poc_finetuned_ud") model = AutoModelForSequenceClassification.from_pretrained("philmunz/poc_finetuned_ud") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f776cf8fc2ca4d9a7bf30943bcf7be58f341e0263646451afe9df3b25da0d737
- Size of remote file:
- 438 MB
- SHA256:
- 62d5ed0047b7110fba57271ec864d8213e893ae63c66f11f2f302a1a1d1eb94f
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