Instructions to use hf-internal-testing/tiny-random-MegatronBertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MegatronBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-MegatronBertForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MegatronBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-MegatronBertForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-MegatronBertForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 890 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-MegatronBertForTokenClassification/resolve/0b7a02121b6eb9356d15c12fbce970bd18c13e08/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MegatronBertForTokenClassification@0b7a02121b6eb9356d15c12fbce970bd18c13e08/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-MegatronBertForTokenClassification/resolve/0b7a02121b6eb9356d15c12fbce970bd18c13e08/pytorch_model.bin
890 kB
- Xet hash:
- 255829876aa8c0ed6ba2786f0df255d7de3bdc1eb7c0631ca036838c18c1e19f
- Size of remote file:
- 890 kB
- SHA256:
- e56d8704d9b8a4850af403590a63df13dfd46e6a230fd0f166bbba14dab8125e
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