Instructions to use connectivity/bert_ft_qqp-40 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-40 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-40")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-40") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-40", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload qqp_eval@34110steps_bert_ft_qqp-40.json with git-lfs
abf026b -
Upload paws_eval@34110steps_bert_ft_qqp-40.json
c41037c -
Upload paws_eval@25000steps_bert_ft_qqp-40.json
2a9b115 -
Upload paws_eval@15000steps_bert_ft_qqp-40.json
efc304e -
Added training logs
5e17fad -
Saving weights and logs of step 34110
aab277c -
Saving weights and logs of step 30000
4525741 -
Saving weights and logs of step 25000
b5b31ee -
Saving weights and logs of step 20000
2ce2791 -
Saving weights and logs of step 15000
0021ed8 -
Saving tokenizer
43181a1 -
initial commit
a2a801a