Instructions to use 1024m/WASSA24-Task1-3a-LLAMA3-8B-AP-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 1024m/WASSA24-Task1-3a-LLAMA3-8B-AP-lora with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("1024m/WASSA24-Task1-3a-LLAMA3-8B-AP-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from 1024m/WASSA24-Task1-3a-LLAMA3-8B-AP-lora: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/1024m/WASSA24-Task1-3a-LLAMA3-8B-AP-lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://1024m/WASSA24-Task1-3a-LLAMA3-8B-AP-lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/1024m/WASSA24-Task1-3a-LLAMA3-8B-AP-lora/resolve/main/tokenizer.json
9.09 MB
File too large to display, you can check the raw version instead.