Instructions to use hf-internal-testing/tiny-random-BertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-BertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-BertForSequenceClassification") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e666f1c42542e06ad096d1274b085359f15022c9bbdb6c9fabfe154c9eb73f3b
- Size of remote file:
- 366 kB
- SHA256:
- 3f6fbc63d73ec4c929ce7ebc46a4cd9080a2539361db460b79b39379c9909592
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