Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use GhylB/Sentiment_Analysis_BERT_Based_MODEL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GhylB/Sentiment_Analysis_BERT_Based_MODEL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GhylB/Sentiment_Analysis_BERT_Based_MODEL")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GhylB/Sentiment_Analysis_BERT_Based_MODEL") model = AutoModelForSequenceClassification.from_pretrained("GhylB/Sentiment_Analysis_BERT_Based_MODEL") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1000
Browse files
pytorch_model.bin
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runs/May07_20-10-46_d2d2afe4bb13/events.out.tfevents.1683490463.d2d2afe4bb13.1596.0
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