Text Classification
Transformers
PyTorch
English
bert
sequence-classification
sentiment-analysis
Eval Results (legacy)
Instructions to use toolathon123/my-awesome-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toolathon123/my-awesome-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="toolathon123/my-awesome-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("toolathon123/my-awesome-model") model = AutoModelForSequenceClassification.from_pretrained("toolathon123/my-awesome-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37f45949bd9cd6c6ddff01ece8abb7ec3193f4a0d131711120efc24afee9ede9
- Size of remote file:
- 19 Bytes
- SHA256:
- 233d3b4142af63234125177a1ea6fc52b545d7e60002f1c955c8ff1d1f8f21c6
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