Instructions to use firebolt/llama_or_what with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use firebolt/llama_or_what with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="firebolt/llama_or_what") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("firebolt/llama_or_what") model = AutoModelForImageClassification.from_pretrained("firebolt/llama_or_what") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf23301ee43f6994b298f466305c7bf7782b954c054d7b9093fd861a4af3ba9c
- Size of remote file:
- 343 MB
- SHA256:
- adba4700af1ae390dbaaf1022bc2fbb13b038ca39b50e6ac03ccb1b22c8e10fa
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