Instructions to use harris1/mistral_7b_multi_label_abstract_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harris1/mistral_7b_multi_label_abstract_classification with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("harris1/mistral_7b_multi_label_abstract_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from harris1/mistral_7b_multi_label_abstract_classification: direct link, hf CLI and curl.
- Browser
- Download file 1.8 MB
-
https://huggingface.co/harris1/mistral_7b_multi_label_abstract_classification/resolve/main/tokenizer.json
- Command line
-
hf download hf://harris1/mistral_7b_multi_label_abstract_classification/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/harris1/mistral_7b_multi_label_abstract_classification/resolve/main/tokenizer.json
1.8 MB
File too large to display, you can check the raw version instead.