Instructions to use hf-tiny-model-private/tiny-random-ConvBertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-ConvBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-ConvBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad820604d51590256b0fe6f3e0443e14eafa62aec35c8a7f74759a808cb18347
- Size of remote file:
- 5.36 MB
- SHA256:
- adfae070d92f5877c7a772bf463644fd6b427e5cab79fd51cf94cafa2b3c7c66
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