Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/roberta_Pfinal_2e-5_16_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fredymad/roberta_Pfinal_2e-5_16_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fredymad/roberta_Pfinal_2e-5_16_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/roberta_Pfinal_2e-5_16_2") model = AutoModelForSequenceClassification.from_pretrained("fredymad/roberta_Pfinal_2e-5_16_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3f02bdf528bf6bb486876407c88439e63c9981509705823422f21581e2635be
- Size of remote file:
- 499 MB
- SHA256:
- d6e12f759eb53c74e28c29b812ce7c5ed1e20f9bff68bd7fbe8ff64bb96e0ec6
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