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:
- 86b7ccea60229a60b0eba840d6c037c1bcbddb940a03c3359f2b521a0a3f1c3b
- Size of remote file:
- 3.9 kB
- SHA256:
- 9fe8c44ab511e52a33b7769d6a7f378d565a27d7680685a2a6c5c62b62f98bda
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