Instructions to use deetsml/HIMsetfitMultiLabelModel2epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deetsml/HIMsetfitMultiLabelModel2epochs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="deetsml/HIMsetfitMultiLabelModel2epochs")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("deetsml/HIMsetfitMultiLabelModel2epochs") model = AutoModel.from_pretrained("deetsml/HIMsetfitMultiLabelModel2epochs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deetsml/HIMsetfitMultiLabelModel2epochs: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/deetsml/HIMsetfitMultiLabelModel2epochs/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://deetsml/HIMsetfitMultiLabelModel2epochs/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deetsml/HIMsetfitMultiLabelModel2epochs/resolve/main/pytorch_model.bin
1.63 GB
- Xet hash:
- 64858a5499fc058719b11604286d363043327f385cb454efa4a9bfb5d51f0468
- Size of remote file:
- 1.63 GB
- SHA256:
- 5bca1bd00ee3fce3f33885d61469d51efb3d13c433b01168020c1242bd0ca2f7
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