Instructions to use Isma/model_45000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isma/model_45000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Isma/model_45000")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Isma/model_45000") model = AutoModel.from_pretrained("Isma/model_45000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d875085db702c9fd817fbd2f430f97cefb1f7584793dd5874031dcfc05ac3a9e
- Size of remote file:
- 378 MB
- SHA256:
- d12537161ba3904e38a0e4caee6fec00a3f989cd5479b65edd4ca720577bb6a0
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