Instructions to use hf-internal-testing/tiny-random-AlbertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-AlbertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-AlbertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-AlbertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-AlbertForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86c5a4cdf8b22611c6fb89549751ddb885a2a1fbf7a4a4e3295b8ac235ce98cf
- Size of remote file:
- 16 MB
- SHA256:
- 77202f3b326aef6fc29608df4fddd6e36c37e1f6ceb5f4853c1590d082e07772
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