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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 826ae95801af734a1ca2a5997ea941a53361b4a46b55c8831076afd6c2b96c12
- Size of remote file:
- 160 kB
- SHA256:
- 09f950f250410b83518bea7eeb8022d32a584b71aeaf8867c0e60c1fa02892dd
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