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:
- 8e5439e5de01c4450552950b2b5ae02c8115d98033383b6df621835096b56ab0
- Size of remote file:
- 32.1 MB
- SHA256:
- 942f795f25f67e622099bae4518fd4357477735b20879b3a96b53b1b3f8e9922
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