Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/roberta_laxo_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_laxo_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_laxo_2e-5_16_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/roberta_laxo_2e-5_16_2") model = AutoModelForSequenceClassification.from_pretrained("fredymad/roberta_laxo_2e-5_16_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8305f9dabd8889ae3fc74800a6e764af1c9cdfbc6b8cbcc8ec06ef411c6ebc6
- Size of remote file:
- 438 MB
- SHA256:
- 34b7a079da0ea3ac551efec505015e943910ca526f96b717e0ab3e886c92e32b
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