Instructions to use PavanDeepak/IAB_Categories_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PavanDeepak/IAB_Categories_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PavanDeepak/IAB_Categories_Classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PavanDeepak/IAB_Categories_Classification") model = AutoModelForSequenceClassification.from_pretrained("PavanDeepak/IAB_Categories_Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from PavanDeepak/IAB_Categories_Classification: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/PavanDeepak/IAB_Categories_Classification/resolve/main/model.safetensors
- Command line
-
hf download hf://PavanDeepak/IAB_Categories_Classification/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/PavanDeepak/IAB_Categories_Classification/resolve/main/model.safetensors
440 MB
- Xet hash:
- f9de307222e8757309570c2e27c938c9172751a1e40358c0cec3f81cc2656839
- Size of remote file:
- 440 MB
- SHA256:
- 6ce647a02bab737f99d743d5d957bd76395afaffc99186857a08337578fe333a
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