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:
- fa80fbe3aac249f317e05a996faa8d3a5ec6babba061d074060f64afb3b2861c
- Size of remote file:
- 2.99 kB
- SHA256:
- c0c1722f7d41344e3f115a356d92a3c8d4d90d0c360a4941d5659483c26a3299
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