Instructions to use hf-internal-testing/tiny-random-ConvBertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ConvBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-ConvBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ConvBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-ConvBertForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d5da54228c803860453b438f170ff70f6206711a1ff0bb19fc09c35e576af17
- Size of remote file:
- 5.54 MB
- SHA256:
- 5174e68038e2ef3a523d99725c809691cc775602d5f845d116682e59111eea4c
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