Instructions to use hf-internal-testing/tiny-random-MT5ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MT5ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-MT5ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MT5ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-MT5ForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ed8e8f3fdbf9e72675833ec9aaf8bb578b04504c4c5608469e3e4e385acc66c
- Size of remote file:
- 32.1 MB
- SHA256:
- b29404d922372dd83bdf539517c08e3f55b0d18fac8b077423108648cc1ced30
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