Instructions to use hf-internal-testing/tiny-random-MegatronBertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MegatronBertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MegatronBertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MegatronBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MegatronBertForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33109c02912109fdbf47a205a4931913e8bcfada39fda55b305b8f4a55be1b73
- Size of remote file:
- 908 kB
- SHA256:
- 17a136dc79e5cbcad373fbd258b1d8ca51b1a04aa94780beb711b19e82c1769c
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