Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/bert_Pfinal_4CLASES_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_4CLASES_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_4CLASES_2e-5_16_10")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/bert_Pfinal_4CLASES_2e-5_16_10") model = AutoModelForSequenceClassification.from_pretrained("fredymad/bert_Pfinal_4CLASES_2e-5_16_10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23b4fb56c7b77051dca708829c7aef90541ed77f8c3afb149f8b5149c88996b5
- Size of remote file:
- 3.64 kB
- SHA256:
- 826fc2590f722e1bbaa8a468beacf395428447092e4f66f174618d2ac6a6f969
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