Instructions to use mrHunghddddd/27a16469-01bc-43b2-8559-6ba116223e0b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mrHunghddddd/27a16469-01bc-43b2-8559-6ba116223e0b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("The-matt/llama2_ko-7b_distinctive-snowflake-182_1060") model = PeftModel.from_pretrained(base_model, "mrHunghddddd/27a16469-01bc-43b2-8559-6ba116223e0b") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from mrHunghddddd/27a16469-01bc-43b2-8559-6ba116223e0b: direct link, hf CLI and curl.
- Browser
- Download file 80 MB
-
https://huggingface.co/mrHunghddddd/27a16469-01bc-43b2-8559-6ba116223e0b/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://mrHunghddddd/27a16469-01bc-43b2-8559-6ba116223e0b/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/mrHunghddddd/27a16469-01bc-43b2-8559-6ba116223e0b/resolve/main/adapter_model.safetensors
80 MB
- Xet hash:
- 6b8a06976827782c8eecf1b53f79113d623672f1559ee6193900fb4e8fc418cb
- Size of remote file:
- 80 MB
- SHA256:
- 2b7358fc829371a481d9e6cb875cd937732805a014bf55222688b74ab4ad60bd
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