Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/distilbert_Pfinal_4CLASES_2e-5_16_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fredymad/distilbert_Pfinal_4CLASES_2e-5_16_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fredymad/distilbert_Pfinal_4CLASES_2e-5_16_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/distilbert_Pfinal_4CLASES_2e-5_16_2") model = AutoModelForSequenceClassification.from_pretrained("fredymad/distilbert_Pfinal_4CLASES_2e-5_16_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e93cf5120b51ad1ebe5debdebb751de323ddb166b4ec5126ca4c8056b361364
- Size of remote file:
- 269 MB
- SHA256:
- 77ab81b9504ac5b4ed8e96b8d48e2fd2958593d775de6ff7e2835d151c396886
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