Text Classification
Transformers
PyTorch
TensorFlow
JAX
English
bert
financial-sentiment-analysis
sentiment-analysis
Instructions to use Ziffirpetek/Text-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ziffirpetek/Text-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ziffirpetek/Text-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ziffirpetek/Text-Classification") model = AutoModelForSequenceClassification.from_pretrained("Ziffirpetek/Text-Classification") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
a76a6be | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:04c231ff252c4b5ed3e277120b1cc961b97be14d81825c51c44ba66b4ee8033e
size 437945404
|