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 model_head.pkl from deetsml/HIMsetfitMultiLabelModel2epochs: direct link, hf CLI and curl.
- Browser
- Download file 309 kB
-
https://huggingface.co/deetsml/HIMsetfitMultiLabelModel2epochs/resolve/main/model_head.pkl
- Command line
-
hf download hf://deetsml/HIMsetfitMultiLabelModel2epochs/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/deetsml/HIMsetfitMultiLabelModel2epochs/resolve/main/model_head.pkl
309 kB
- Xet hash:
- 0b4ad5a0f3a3fde093de093768bc37f885f40f911552171cdb20bbed930778e6
- Size of remote file:
- 309 kB
- SHA256:
- 5417f51a0ab0878dc0abd7218cf1c58f35626ccb6dc94a4e6f7ca51ec4aebf8c
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