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:
- 5261e446808d29a8596c6d0a33cf1b2c92419d3760bf633186106e40bc583e01
- Size of remote file:
- 17.6 MB
- SHA256:
- 015f998c110fd39aaf6993b9574820539c0bc004d6bc5c04200d1fb93bea0b25
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