Instructions to use hf-internal-testing/tiny-random-RobertaForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RobertaForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-RobertaForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RobertaForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-RobertaForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-RobertaForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 367 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-RobertaForTokenClassification/resolve/8d1ab12af459cbff5413834257ed87d9e7efb359/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-RobertaForTokenClassification@8d1ab12af459cbff5413834257ed87d9e7efb359/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-RobertaForTokenClassification/resolve/8d1ab12af459cbff5413834257ed87d9e7efb359/pytorch_model.bin
367 kB
- Xet hash:
- af9645873cbe5edad3765fe8794a2570b7fc81fa40e4f750b07fef68be4566dd
- Size of remote file:
- 367 kB
- SHA256:
- 672990ecf4faebfe264f5769229a655f53dbb2a5389537da39339f7299e96bb4
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