Instructions to use hf-internal-testing/tiny-random-MistralForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MistralForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MistralForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MistralForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MistralForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e46f8ef2596ebef3adf0911d7d774cf21a18eec6f622cac3b7c0e8752e0bf218
- Size of remote file:
- 4.15 MB
- SHA256:
- ebe51f1ca55298f086b592f896b4d6420069aaa330a775d3e1910fd1270ee5c6
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