Instructions to use squadgoals404/Image_Audio_Text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use squadgoals404/Image_Audio_Text with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="squadgoals404/Image_Audio_Text")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("squadgoals404/Image_Audio_Text") model = AutoModelForSequenceClassification.from_pretrained("squadgoals404/Image_Audio_Text", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f6927019fc30f59251abf9b2582bdc3c4aa5be1c17e95b32d263b7def44169f
- Size of remote file:
- 1.11 GB
- SHA256:
- 80e91561ada159db73f41073c6ca45d5fcdb4d27950c0a36ad0a3a7d794fabbc
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