Instructions to use hf-internal-testing/tiny-random-MPNetForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MPNetForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-MPNetForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MPNetForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-MPNetForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3df6c23ae9e7aa0353b05a41d58bf360ee2843b9095b32ce7dceb0f8bb6c95d0
- Size of remote file:
- 1.03 MB
- SHA256:
- 44df79cee319048b6fc17a7100486a5eca7992cf9007197f456c6496ee15792f
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