Instructions to use connectivity/bert_ft_qqp-55 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-55 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-55")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-55") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-55", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload qqp_eval@34110steps_bert_ft_qqp-55.json with git-lfs
d9f29c1 -
Upload paws_eval@34110steps_bert_ft_qqp-55.json
4640e64 -
Upload paws_eval@25000steps_bert_ft_qqp-55.json
e6c1610 -
Upload paws_eval@15000steps_bert_ft_qqp-55.json
9225f99 -
Added training logs
64dd437 -
Saving weights and logs of step 34110
9b05bbf -
Saving weights and logs of step 30000
0cc75dc -
Saving weights and logs of step 25000
55efdef -
Saving weights and logs of step 20000
79d2fe7 -
Saving weights and logs of step 15000
bc9e98e -
Saving tokenizer
23b3218 -
initial commit
44f7a6f