Instructions to use VictorDCh/Llama-3-8B-Instruct-spider-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use VictorDCh/Llama-3-8B-Instruct-spider-4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct") model = PeftModel.from_pretrained(base_model, "VictorDCh/Llama-3-8B-Instruct-spider-4") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from VictorDCh/Llama-3-8B-Instruct-spider-4: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/VictorDCh/Llama-3-8B-Instruct-spider-4/resolve/main/training_args.bin
- Command line
-
hf download hf://VictorDCh/Llama-3-8B-Instruct-spider-4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/VictorDCh/Llama-3-8B-Instruct-spider-4/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- e309cdcbfef567c91b026d8afa486285ffdcd66a17643988dd4e91e05685ba94
- Size of remote file:
- 5.05 kB
- SHA256:
- 34f21c628e0942ad4216a575e79648cfc7a1019379c7d4684f4bcdea6ca17031
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