Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use OliverHeine/roberta-base_train_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/roberta-base_train_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/roberta-base_train_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/roberta-base_train_v1") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/roberta-base_train_v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ecfb16c1474da7125c1252614f9e4092f12b0a19c7b9d39e4b5a764aeb98b5e8
- Size of remote file:
- 499 MB
- SHA256:
- 946326b7c026e5883d71e69fc210cad69c562e5c94d16c8ef3e4d0cb2d6b9bb8
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