Instructions to use hf-tiny-model-private/tiny-random-RobertaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-RobertaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-RobertaForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RobertaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-RobertaForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4e516148407bf1ab34d207ee9398cb25068b9abd9259354014e46527ddfd12c
- Size of remote file:
- 467 kB
- SHA256:
- 1885eb07b25ec71df9f7e8b0b78fd5bc410cf84bf86d6ea82856216700770eda
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