Instructions to use AnonymousSub/dummy_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousSub/dummy_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousSub/dummy_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousSub/dummy_1") model = AutoModelForSequenceClassification.from_pretrained("AnonymousSub/dummy_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e6cd47e1be9ba35ceb9b8fee670d1b133a9afbf4286e562b8203bea57cf5476
- Size of remote file:
- 1.42 GB
- SHA256:
- 4db2144ade686c6eae193e89cb6c8d58827e094f74d5079b9e1d2819c9349dbc
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