Instructions to use YakovElm/Qt_10_RoBERTa_Over_Sampling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Qt_10_RoBERTa_Over_Sampling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Qt_10_RoBERTa_Over_Sampling")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Qt_10_RoBERTa_Over_Sampling") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Qt_10_RoBERTa_Over_Sampling") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:7e0b2ed9a4929d406b5e7fb511cd7a29a8a26373a1de16c4542e526c6253d6dc
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size 498617024
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