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
File size: 67 Bytes
c7b3a4a | 1 2 3 4 | {
"model_max_length": 512,
"tokenizer_class": "BertTokenizer"
} |