Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use xqchq/TextClassificationTHUCNews with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xqchq/TextClassificationTHUCNews with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xqchq/TextClassificationTHUCNews")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xqchq/TextClassificationTHUCNews") model = AutoModelForSequenceClassification.from_pretrained("xqchq/TextClassificationTHUCNews") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f192c7f5336bc1ec7e1f3cb6e0b751a8621735d1e2906e8ab53ed0e25cd1396
- Size of remote file:
- 3.64 kB
- SHA256:
- 55c73d971d00139690caf060957efc407639df50b06233ce5283c53a171a4e03
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.