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:
- a0591cd84754b406629071b8a0b3d519d75d6c78abaa942f0c71f742c3c97f40
- Size of remote file:
- 15.9 MB
- SHA256:
- 404a5a7fb8169fbb705fdd58c523f9d81b9eff18142d2669e658fcb2828eba6b
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