Instructions to use EmotiScan/amazon-comments-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EmotiScan/amazon-comments-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EmotiScan/amazon-comments-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EmotiScan/amazon-comments-bert") model = AutoModelForSequenceClassification.from_pretrained("EmotiScan/amazon-comments-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload 20 files
Verified signature9afbbc1 -
Delete emoticon-model.bin
Verified signatureaa0ccda -
Upload 114 files
Verified signatureCorrected model with epochs = 101788594
-
Upload 11 files
Verified signatureTraining checkpoints4f25a2a
-
Create README.md
Verified signature582d183 -
Upload 2 files
Verified signatureThis BERT model is based on google/bert-large-uncased model.832c9d2 -
initial commit
Verified signature211bf51