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:
- e316ea4e39dfed7a95b770c2bd52e73bcba03ada7f377bcb757b3f7985b10a14
- Size of remote file:
- 439 MB
- SHA256:
- b9ac93d10ef7d80a90f8f842dd3dfc2a0b38d1e11f98817b0adaf2e37c6225f1
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