Instructions to use connectivity/bert_ft_qqp-50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-50")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-50") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload qqp_eval@34110steps_bert_ft_qqp-50.json with git-lfs
1a54e50 -
Upload paws_eval@34110steps_bert_ft_qqp-50.json
def4c13 -
Upload paws_eval@25000steps_bert_ft_qqp-50.json
eda8ff5 -
Upload paws_eval@15000steps_bert_ft_qqp-50.json
26b8b64 -
Added training logs
7086abc -
Saving weights and logs of step 34110
0e3df00 -
Saving weights and logs of step 30000
c8c7a29 -
Saving weights and logs of step 25000
daeb7ed -
Saving weights and logs of step 20000
7e73611 -
Saving weights and logs of step 15000
82b9985 -
Saving tokenizer
a053c23 -
initial commit
14c678c