Instructions to use HuggingFaceH4/tiny-random-LlamaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuggingFaceH4/tiny-random-LlamaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HuggingFaceH4/tiny-random-LlamaForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/tiny-random-LlamaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("HuggingFaceH4/tiny-random-LlamaForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HuggingFaceH4/tiny-random-LlamaForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 2.09 MB
-
https://huggingface.co/HuggingFaceH4/tiny-random-LlamaForSequenceClassification/resolve/5ce65cd8e9a5893055fac24989b8e3d32cfdb79f/pytorch_model.bin
- Command line
-
hf download hf://HuggingFaceH4/tiny-random-LlamaForSequenceClassification@5ce65cd8e9a5893055fac24989b8e3d32cfdb79f/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/HuggingFaceH4/tiny-random-LlamaForSequenceClassification/resolve/5ce65cd8e9a5893055fac24989b8e3d32cfdb79f/pytorch_model.bin
2.09 MB
- Xet hash:
- e98de27172dc581d0c583fb5f57c81707e9c4c7eef056a28c7d4725900070ce3
- Size of remote file:
- 2.09 MB
- SHA256:
- aa39804418ed1893d83ad16ed60cbbb67533a000d359ca110d2721b0e87224d4
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