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:
- 2a2cdb1c96e3dca5bb8aaf239d92f4f1e10e8ba6cb754d49efe66b8eb0b86743
- Size of remote file:
- 179 kB
- SHA256:
- e77a64f553b54a535c4f098e5102fd619fc90cb14039d9b9071efd2919d652ed
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