Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use BiggieW/classification_chnsenticorp_eda_aug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BiggieW/classification_chnsenticorp_eda_aug with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BiggieW/classification_chnsenticorp_eda_aug")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BiggieW/classification_chnsenticorp_eda_aug") model = AutoModelForSequenceClassification.from_pretrained("BiggieW/classification_chnsenticorp_eda_aug") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6cd2485e21637ab219bdda7dcc2c038aac9d72367ff92600e7a0d324a1f9854c
- Size of remote file:
- 3.45 kB
- SHA256:
- ae76cfd7e4a0155c8e88c56e91d7950246d208e36474cd8d5b9bf21ff919ddff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.