Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use KingAsiedu/tweet_sentiments_analysis_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KingAsiedu/tweet_sentiments_analysis_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KingAsiedu/tweet_sentiments_analysis_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KingAsiedu/tweet_sentiments_analysis_bert") model = AutoModelForSequenceClassification.from_pretrained("KingAsiedu/tweet_sentiments_analysis_bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bc97ad3d05c4515a03b7573d71720e8bb9c48089976cc096fbd0a1992eb4e7f
- Size of remote file:
- 433 MB
- SHA256:
- 5d1b2f75b6a5dd7367af49ae8011bcdd2b6ae3544d1a443184e77ee7a51a134c
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