Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-53 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/std_0pnt2_bert_ft_cola-53 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/std_0pnt2_bert_ft_cola-53")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-53") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-53", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Added training logs
60a94d0 -
Saving weights and logs of step 1603
718b064 -
Saving weights and logs of step 1600
db06a2a -
Saving weights and logs of step 1500
d3487a7 -
Saving weights and logs of step 1400
65c8e9e -
Saving weights and logs of step 1300
3e0102a -
Saving weights and logs of step 1200
844c720 -
Saving weights and logs of step 1100
933f26f -
Saving weights and logs of step 1000
0940557 -
Saving weights and logs of step 900
045a09d -
Saving weights and logs of step 800
c716416 -
Saving weights and logs of step 700
888ffc1 -
Saving weights and logs of step 600
5359790 -
Saving weights and logs of step 500
87238c4 -
Saving weights and logs of step 400
02f4a66 -
Saving weights and logs of step 300
2c4b416 -
Saving weights and logs of step 200
57e6562 -
Saving weights and logs of step 100
8724dc6 -
Saving weights and logs of step 0
2f2d5bd -
Saving tokenizer
69a0d0b -
initial commit
d4c584f