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:
- 48dd9a1049d7db7983da18868e87c2b9031c30176ad41cd049593a967b6be572
- Size of remote file:
- 3.18 kB
- SHA256:
- 98cfc50532afbaac8c32af2e9e27d82df7a55c33cd3c4c9597066b7acdca94d6
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