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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0fa0df6afd0a579bc7abf32629a2485ec4f83d3b9b791f83e4d7dfbb8c54a3ef
- Size of remote file:
- 4.15 MB
- SHA256:
- 656d35c86e274dfab2f5c803d684c995825e4b61a20d94bb63c22ba313e806f0
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