Instructions to use HuggingFaceH4/tiny-random-LlamaForSeqClass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuggingFaceH4/tiny-random-LlamaForSeqClass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HuggingFaceH4/tiny-random-LlamaForSeqClass")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/tiny-random-LlamaForSeqClass") model = AutoModelForSequenceClassification.from_pretrained("HuggingFaceH4/tiny-random-LlamaForSeqClass") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e241e91e075cb1639b9c3e103a3a59a4dbdb97b91b3336eb03165d5bfee497a
- Size of remote file:
- 2.08 MB
- SHA256:
- 7d1a9be2ac5d373e4f2a5effd9c7837cb0d717eea7a78ca27227b910f047d7af
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