Instructions to use Miladsaeedi70/First_practice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Miladsaeedi70/First_practice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Miladsaeedi70/First_practice")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Miladsaeedi70/First_practice") model = AutoModel.from_pretrained("Miladsaeedi70/First_practice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0d13bff2d7d9a9805032eb5e25bb0454391ff517375d9aa3ee27bcc6f374f88
- Size of remote file:
- 433 MB
- SHA256:
- 94908f055f78ac319b4de3c8855c21008b25707bd8d0627643927504b8927765
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