Instructions to use hf-tiny-model-private/tiny-random-MegaForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MegaForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-MegaForTokenClassification")# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-MegaForTokenClassification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fefbf006fa7e59ec1a8af406b8cfbbcb85b30d7394e3cfed4037ee6de7bd2b48
- Size of remote file:
- 382 kB
- SHA256:
- b09177217d71a4b14f0b38d6bccad459f4ca524ad70c8573e254e84250097973
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