Instructions to use Jeevesh8/init_bert_ft_qqp-20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-20 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-20")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-20") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-20", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Added training logs
5c448e8 -
Saving weights and logs of step 34110
cdb4175 -
Saving weights and logs of step 30000
96bf24a -
Saving weights and logs of step 25000
eff8540 -
Saving weights and logs of step 20000
3231bed -
Saving weights and logs of step 15000
36cfdcb -
Saving tokenizer
bc8b181 -
initial commit
98848f6