Instructions to use DjangoDeng/llama2-test-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DjangoDeng/llama2-test-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "DjangoDeng/llama2-test-lora") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from DjangoDeng/llama2-test-lora: direct link, hf CLI and curl.
- Browser
- Download file 16.8 MB
-
https://huggingface.co/DjangoDeng/llama2-test-lora/resolve/main/adapter_model.bin
- Command line
-
hf download hf://DjangoDeng/llama2-test-lora/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/DjangoDeng/llama2-test-lora/resolve/main/adapter_model.bin
16.8 MB
- Xet hash:
- 25f42193c48031ffe98215927048b0064a6451ece18248b30b7f4476b1fa1891
- Size of remote file:
- 16.8 MB
- SHA256:
- b5afb932fb432ccf9b5d24b0eeff795d250f04e9270f691a16acbe5364181931
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