Instructions to use nhung01/747e0590-b54d-4dbd-a93b-a7978a208caa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung01/747e0590-b54d-4dbd-a93b-a7978a208caa 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, "nhung01/747e0590-b54d-4dbd-a93b-a7978a208caa") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from nhung01/747e0590-b54d-4dbd-a93b-a7978a208caa: direct link, hf CLI and curl.
- Browser
- Download file 80.1 MB
-
https://huggingface.co/nhung01/747e0590-b54d-4dbd-a93b-a7978a208caa/resolve/main/adapter_model.bin
- Command line
-
hf download hf://nhung01/747e0590-b54d-4dbd-a93b-a7978a208caa/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/nhung01/747e0590-b54d-4dbd-a93b-a7978a208caa/resolve/main/adapter_model.bin
80.1 MB
- Xet hash:
- 59f0409d1c2002803fabb4ef364219c5e84af082bb49e9fdf655dcfa20ff6802
- Size of remote file:
- 80.1 MB
- SHA256:
- f691fc6962ebbd4ccc9f64848053a5d65811b9699f46efc9e3dfd673ee5bcef4
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