Instructions to use connectivity/bert_ft_qqp-51 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-51 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-51")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-51") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-51", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload qqp_eval@34110steps_bert_ft_qqp-51.json with git-lfs
ffeb2e4 -
Upload paws_eval@34110steps_bert_ft_qqp-51.json
9455327 -
Upload paws_eval@25000steps_bert_ft_qqp-51.json
7aa41e6 -
Upload paws_eval@15000steps_bert_ft_qqp-51.json
ed9e5eb -
Added training logs
c4575c0 -
Saving weights and logs of step 34110
219644b -
Saving weights and logs of step 30000
c234803 -
Saving weights and logs of step 25000
003cc15 -
Saving weights and logs of step 20000
8944485 -
Saving weights and logs of step 15000
9e2e8b1 -
Saving tokenizer
f61dc2c -
initial commit
487a101