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 model.safetensors from hf-internal-testing/tiny-random-MegatronBertForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 872 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-MegatronBertForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MegatronBertForTokenClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-MegatronBertForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
872 kB
- Xet hash:
- c4e1be3a72b355d2c5fab7977efa5f1432108c9afca2c4f7db7ae7e4f57c64a6
- Size of remote file:
- 872 kB
- SHA256:
- adc1d52b525d79ff1c110e7d478ba1bf0a9514d29dd3dc1bff0965eedc96d9fd
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