Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Lorenzo1708/TC01_Trabalho01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lorenzo1708/TC01_Trabalho01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Lorenzo1708/TC01_Trabalho01")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Lorenzo1708/TC01_Trabalho01") model = AutoModelForSequenceClassification.from_pretrained("Lorenzo1708/TC01_Trabalho01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cab38479c385e7993f3fe8e3a68abe0ec8c74a96021ec06c72793735aa90ef61
- Size of remote file:
- 268 MB
- SHA256:
- be493cc5465f47b5578246c98362231ad6217cfb5ccadac8220d0ac4fbeedb4d
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