Instructions to use YsnHdn/Model_PFE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YsnHdn/Model_PFE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YsnHdn/Model_PFE")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YsnHdn/Model_PFE") model = AutoModelForSequenceClassification.from_pretrained("YsnHdn/Model_PFE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82d38f95d592f8fc08efc5aa338934e3d291416c5ddd13e582257475833b5c4d
- Size of remote file:
- 438 MB
- SHA256:
- 77e959fadc3a09d85fa46103e4ada68e827b0a2cc64bdd660c600e2999433e27
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