Instructions to use Isma/v2_50k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isma/v2_50k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Isma/v2_50k")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Isma/v2_50k") model = AutoModel.from_pretrained("Isma/v2_50k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25f24983c0c3e0f515316fdde30cc7d4c3a5dfe9b237c116366e3b1911ed3de8
- Size of remote file:
- 378 MB
- SHA256:
- 0f994e4613c500fb2f540319290e6c91b08f0e64655d588f84c92cd31700cfaf
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