Instructions to use SOUMYADEEPSAR/bert_transfer2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SOUMYADEEPSAR/bert_transfer2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SOUMYADEEPSAR/bert_transfer2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SOUMYADEEPSAR/bert_transfer2") model = AutoModelForSequenceClassification.from_pretrained("SOUMYADEEPSAR/bert_transfer2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69eade191b514783997f40438cef76f16b221d498703202087e5de86fe5d8d1c
- Size of remote file:
- 433 MB
- SHA256:
- 7d77346c2d34034d75e47fc01cf35325cbd5f92208dc2d63a8881651b3a9ba95
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