Instructions to use yangwang825/bert-base-uncased-mean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yangwang825/bert-base-uncased-mean with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yangwang825/bert-base-uncased-mean", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yangwang825/bert-base-uncased-mean", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("yangwang825/bert-base-uncased-mean", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f2f51fac617931847130a3f9cf3f4ff67a03063f4d0510465980f3ba3e8e439
- Size of remote file:
- 438 MB
- SHA256:
- b0e4d45385d6072711fe037338b7d41b4c82e7310bfec45c493ee84f649432b7
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