Instructions to use EhsanAghazadeh/bert-based-uncased-sst2-e6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EhsanAghazadeh/bert-based-uncased-sst2-e6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EhsanAghazadeh/bert-based-uncased-sst2-e6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EhsanAghazadeh/bert-based-uncased-sst2-e6") model = AutoModelForSequenceClassification.from_pretrained("EhsanAghazadeh/bert-based-uncased-sst2-e6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6a0813090525cb3fe7f505e1f2ae264a00ef10fddad2fd0048b66dea9597fb2
- Size of remote file:
- 876 MB
- SHA256:
- 5d115ff9ff690b105acfff46ef576ae573d13e0edbd3bf639a78ab77fa1e3729
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