Instructions to use hf-internal-testing/tiny-random-IBertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-IBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-IBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-IBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-IBertForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fa75013564abb5282b6953b16c4f83583dadc1f604e9b92621c6ac05d2314b0
- Size of remote file:
- 813 kB
- SHA256:
- 3e29bf43f89e024f2de4040f763ba97d247295a3bf85e7942a23146ec88a405d
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