Instructions to use YakovElm/Qt_15_BERT_Over_Sampling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Qt_15_BERT_Over_Sampling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Qt_15_BERT_Over_Sampling")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Qt_15_BERT_Over_Sampling") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Qt_15_BERT_Over_Sampling") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67cab213a085b9827e6775cf2889fca93179e38c86c3e4056a346063ffa68f6c
- Size of remote file:
- 438 MB
- SHA256:
- c2463e57341442b5f4f8a1ba66aaa9621dfa7288c3b52674dc2d37bc769085b5
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