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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3e3064d9429c0e0b7ed19735527f4ae5e4c961aa6d2added013bdaa51fe1f27
- Size of remote file:
- 16.5 MB
- SHA256:
- 40ca9f2afc67c230cfe5513fe038e3538a2f111cccf5c5aac82db24b63fbb884
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