Instructions to use Capreolus/bert-base-msmarco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Capreolus/bert-base-msmarco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Capreolus/bert-base-msmarco")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Capreolus/bert-base-msmarco") model = AutoModelForSequenceClassification.from_pretrained("Capreolus/bert-base-msmarco") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23e744be95ff48b57d4f7b2a07c428198f5601b124eaa5686fc5357cfa8d8d73
- Size of remote file:
- 438 MB
- SHA256:
- 9e8e9261d45b163f4ada6bfb820f63972068879f7d13e391c525910c9a67b8b8
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