Instructions to use Kal1510/LLMRecoveryLLama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Kal1510/LLMRecoveryLLama with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/kaggle/input/llama-2/pytorch/7b-chat-hf/1") model = PeftModel.from_pretrained(base_model, "Kal1510/LLMRecoveryLLama") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Kal1510/LLMRecoveryLLama: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/Kal1510/LLMRecoveryLLama/resolve/main/training_args.bin
- Command line
-
hf download hf://Kal1510/LLMRecoveryLLama/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Kal1510/LLMRecoveryLLama/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 35b4500d31e95825adc4e0a07c95924e6499f47fd500a564bc9bd0db95ac9716
- Size of remote file:
- 4.92 kB
- SHA256:
- cf83471da6840d05ff6da871c3357d07754c7283be20430ecb150c59ec1d3194
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