Instructions to use palakagl/bert_TextClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use palakagl/bert_TextClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="palakagl/bert_TextClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("palakagl/bert_TextClassification") model = AutoModelForSequenceClassification.from_pretrained("palakagl/bert_TextClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 26e44046fb751626be844da82a933f893bff2e92b75fba2f9c4821a1c6792807
- Size of remote file:
- 433 MB
- SHA256:
- 0491ec42357f065896c1950b3c59c52eb7c14232c9f32faf0d2ac1b8b6ea14e4
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