Instructions to use autonomous019/bert_small_uncased_512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autonomous019/bert_small_uncased_512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="autonomous019/bert_small_uncased_512")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("autonomous019/bert_small_uncased_512") model = AutoModelForSequenceClassification.from_pretrained("autonomous019/bert_small_uncased_512") - Notebooks
- Google Colab
- Kaggle
a lightweight solution for the Kaggle ELL competition using google/bert_uncased_L-4_H-256_A-4
Info about the Kaggle ELL competition: https://www.kaggle.com/competitions/feedback-prize-english-language-learning/code
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