Instructions to use hf-internal-testing/tiny-random-MraForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MraForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-MraForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MraForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-MraForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bb11c93f35600fdf5ed850ec83da3cc846c12e43e03a4df8701a7d90428cfc0
- Size of remote file:
- 179 kB
- SHA256:
- 993f225a7867a94de1bdbb3a631d488617ed60c8a58327030b4a02f5cfca5da8
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