Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/bert_Pfinal_2e-5_16_10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fredymad/bert_Pfinal_2e-5_16_10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fredymad/bert_Pfinal_2e-5_16_10")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/bert_Pfinal_2e-5_16_10") model = AutoModelForSequenceClassification.from_pretrained("fredymad/bert_Pfinal_2e-5_16_10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 719d06c0795773162c3137318c91d30fd57853f6b9a9c374102efa512f04e444
- Size of remote file:
- 439 MB
- SHA256:
- 07ffebe5e629267a26ebfe80e3fa2a898f1902a184a5855e479e89a63a899cdb
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