Instructions to use SOUMYADEEPSAR/convbert_transfer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SOUMYADEEPSAR/convbert_transfer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SOUMYADEEPSAR/convbert_transfer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SOUMYADEEPSAR/convbert_transfer") model = AutoModelForSequenceClassification.from_pretrained("SOUMYADEEPSAR/convbert_transfer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5630054638738a8ac0f6df133acd8fd4f407e708fb35e444865ebe6a3edac563
- Size of remote file:
- 425 MB
- SHA256:
- 0f4db6bad02851af8929692680087dc97531eaf732944ee2f1ba467ff92ea54c
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