Instructions to use hf-internal-testing/tiny-random-RobertaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RobertaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-RobertaForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RobertaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-RobertaForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4604fc305d7f7979b7e31487a58033a27a2f023667014bfb0e31d5cc19d41319
- Size of remote file:
- 459 kB
- SHA256:
- e4261a029ef5738df95aa2b32b57f7d757f8527d9e19f643d4bcaffceaf6dfe9
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