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:
- 8cad5999e14d54d443dddf80ce00fc2bc9b4332210db96a8606b2354e4a86fee
- Size of remote file:
- 33.6 MB
- SHA256:
- a08417464150d1a1e572f8b106fbc0fd1226a64d863d737a4e67a140577965fe
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