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")# pip install -U transformers accelerate # 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
Download pytorch_model.bin from hf-internal-testing/tiny-random-ConvBertForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 5.36 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-ConvBertForTokenClassification/resolve/e94c2cf6109a4f0a05986bb1e0ae633fe7efa2e6/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-ConvBertForTokenClassification@e94c2cf6109a4f0a05986bb1e0ae633fe7efa2e6/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-ConvBertForTokenClassification/resolve/e94c2cf6109a4f0a05986bb1e0ae633fe7efa2e6/pytorch_model.bin
5.36 MB
- Xet hash:
- 0dac222de34d13f86c074d2bc71d84f9ed5e272d130de0b41a0c6e06e50c0bba
- Size of remote file:
- 5.36 MB
- SHA256:
- e9da47bf24cbcabf0c2bb105e9bd2e5dfccf5296daf6b3e1853b700677873883
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