Instructions to use hf-internal-testing/tiny-random-XmodForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XmodForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-XmodForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XmodForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-XmodForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e111e48fba234d397a5cf71bb9e302c98255a4f990d788c89406a88b3672d7ec
- Size of remote file:
- 32.3 MB
- SHA256:
- d06ad61b0840018741b8f59b53e7b9507ad3c8ed3edd5f168d6daaeb5da44cf3
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