Instructions to use research-dump/tiny_bert_temp_classifier_bootstrapped with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/tiny_bert_temp_classifier_bootstrapped with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/tiny_bert_temp_classifier_bootstrapped")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/tiny_bert_temp_classifier_bootstrapped") model = AutoModelForSequenceClassification.from_pretrained("research-dump/tiny_bert_temp_classifier_bootstrapped", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68d133ebdc99e1f2a9ecee6c826a75791544f528753439ab5bed9b17ce7bac9d
- Size of remote file:
- 17.6 MB
- SHA256:
- 42e62b900d5f9bf882d28e6281c4c02cb3b30a7aedbbd9f934bfe78a6a0ff721
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