Instructions to use Ojeda01/bert_base_cased_MultiClass_Sentiment_A with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ojeda01/bert_base_cased_MultiClass_Sentiment_A with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ojeda01/bert_base_cased_MultiClass_Sentiment_A")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ojeda01/bert_base_cased_MultiClass_Sentiment_A") model = AutoModelForSequenceClassification.from_pretrained("Ojeda01/bert_base_cased_MultiClass_Sentiment_A") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1500
Browse files
pytorch_model.bin
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runs/Feb23_15-36-50_2e57ba30445e/events.out.tfevents.1677166620.2e57ba30445e.511.4
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