Instructions to use hf-internal-testing/tiny-random-EsmForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-EsmForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-EsmForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-EsmForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-EsmForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 691ad4e60e295e4d2911c11a21741822f02d47e37a459630ec335b6a1715f790
- Size of remote file:
- 224 kB
- SHA256:
- 40458546747811348d14905e8f1b5492b925a586bc354a22062b4e9e86ee39a3
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