Instructions to use abshafi2021/bdbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abshafi2021/bdbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abshafi2021/bdbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abshafi2021/bdbert") model = AutoModelForSequenceClassification.from_pretrained("abshafi2021/bdbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a656449584be1a8852f215d9c7e1ee57e593d00387abd60c2c484c9959511a0f
- Size of remote file:
- 443 MB
- SHA256:
- 78cea307b6fe8224d7e4116d12c51a0f584fda871af48ff06f28a8e9231527e8
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