Instructions to use hf-internal-testing/tiny-random-PersimmonForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PersimmonForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-PersimmonForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PersimmonForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-PersimmonForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 763c11a0952d2566c4590effd6a9c6ee6b2141e287d72b90a5dd88d327258abe
- Size of remote file:
- 33.6 MB
- SHA256:
- f38febecd82eebf28451d99588f3f1dbb1d0b72b2db875a6280e9f39212a41ae
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