Instructions to use Daksh1/multi_label_LoRA_weights_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Daksh1/multi_label_LoRA_weights_2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Daksh1/multi_label_LoRA_weights_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from Daksh1/multi_label_LoRA_weights_2: direct link, hf CLI and curl.
- Browser
- Download file 4.24 MB
-
https://huggingface.co/Daksh1/multi_label_LoRA_weights_2/resolve/main/tokenizer.model
- Command line
-
hf download hf://Daksh1/multi_label_LoRA_weights_2/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/Daksh1/multi_label_LoRA_weights_2/resolve/main/tokenizer.model
4.24 MB
- Size of remote file:
- 4.24 MB
- SHA256:
- 61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
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