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:
- 77a10d19d1a0fbc93bcb41caf466fc456bc623ba403d8c3c03218d018556c59e
- Size of remote file:
- 242 kB
- SHA256:
- 539564f4ef16c6fac856303cf19e20047842b5922b204fc1adde0c7e33549b49
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